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Zhang X, Wang Y, Yang X, Yang Y. The spontaneous activities of the multiple demand network are related to individual differences in indirect replies comprehension. Behav Brain Res 2024; 469:115021. [PMID: 38692358 DOI: 10.1016/j.bbr.2024.115021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/16/2024] [Accepted: 04/26/2024] [Indexed: 05/03/2024]
Abstract
This study aims to investigate the brain networks engaged in the comprehension of indirect language, as well as the individual difference in this capacity. Specially, we aim to determine whether the difference is solely influenced by the difference in individuals' default network (DN)/language network or whether it also relies on the networks associated with processing of complex cognitive tasks, particularly the multiple demand network (MDN). Conversational indirectness scale (CIS) scores in the interpretation dimension were used as a behavioral indicator of the indirect comprehension tendency. Reading time difference between indirect replies and direct replies collected through a self-paced reading experiment was deemed as a behavioral indicator of comprehension speed of indirect replies comprehension. The two behavioral indicators were combined with resting-state functional magnetic resonance imaging (rs-fMRI). The behaviour-rfMRI analysis showed that ALFF value of right SPL and the functional connectivity (FC) between the right SPL and right IPL/SMA/ITG/Precuneus/bilateral IFG were positively correlated with the interpretation dimension of CIS scores. In addition, the ALFF value of right fusiform gyrus, the FC between the right fusiform gyrus and right precuneus, and the FCs between right SPL and right IPL/Precuneus/IFG were negatively correlated with indirect replies comprehension speed. Overlapping of these regions with large-scale brain network revealed that the right SPL was mainly located in the MDN, and the right fusiform gyrus was mainly located in the language network. Additionally, the areas showing functional connectivity with these regions were primarily located in the MDN, with a smaller subset located in the DN. Our findings suggest that the ability of individuals to actively and rapidly acquire indirect meaning relies not only on the support of the DN and the language network, but also requires collective support from the MDN.
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Affiliation(s)
- Xiuping Zhang
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Yizhu Wang
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Xiaohong Yang
- Department of Psychology, Renmin University of China, Beijing 100872, China; Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, China.
| | - Yufang Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
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2
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Day TKM, Hermosillo R, Conan G, Randolph A, Perrone A, Earl E, Byington N, Hendrickson TJ, Elison JT, Fair DA, Feczko E. Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample. Dev Cogn Neurosci 2024; 66:101355. [PMID: 38354531 PMCID: PMC10875197 DOI: 10.1016/j.dcn.2024.101355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 01/06/2024] [Accepted: 02/03/2024] [Indexed: 02/16/2024] Open
Abstract
Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term "Wernicke's area" near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.
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Affiliation(s)
- Trevor K M Day
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
| | - Robert Hermosillo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Gregory Conan
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Anita Randolph
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Eric Earl
- Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Timothy J Hendrickson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Damien A Fair
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
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Campbell JM, Kundu B, Lee JN, Miranda M, Arain A, Taussky P, Grandhi R, Rolston JD. Evaluating the concordance of functional MRI-based language lateralization and Wada testing in epilepsy patients: A single-center analysis. Interv Neuroradiol 2023; 29:599-604. [PMID: 35979608 PMCID: PMC10549711 DOI: 10.1177/15910199221121384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/20/2022] [Accepted: 08/03/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND For patients with drug-resistant epilepsy, surgery may be effective in controlling their disease. Surgical evaluation may involve localization of the language areas using functional magnetic resonance imaging (fMRI) or Wada testing. We evaluated the accuracy of task-based fMRI versus Wada-based language lateralization in a cohort of our epilepsy patients. METHODS In a single-center, retrospective analysis, we identified patients with medically intractable epilepsy who participated in presurgical language mapping (n = 35) with fMRI and Wada testing. Demographic variables and imaging metrics were obtained. We calculated the laterality index (LI) from task-evoked fMRI activation maps across language areas during auditory and reading tasks to determine lateralization. Possible scores for LI range from -1 (strongly left-hemisphere dominant) to 1 (strongly right-hemisphere dominant). Concordance between fMRI and Wada was estimated using Cohen's Kappa coefficient. Association between the LI scores from the auditory and reading tasks was tested using Spearman's rank correlation coefficient. RESULTS The fMRI-based laterality indices were concordant with results from Wada testing in 91.4% of patients during the reading task (κ = .55) and 96.9% of patients during the auditory task (κ = .79). The mean LIs for the reading and auditory tasks were -0.52 ± 0.43 and -0.68 ± 0.42, respectively. The LI scores for the language and reading tasks were strongly correlated, r(30) = 0.57 (p = 0.001). CONCLUSION Our findings suggest that fMRI is generally an accurate, low-risk alternative to Wada testing for language lateralization. However, when fMRI indicates atypical language lateralization (e.g., bilateral dominance), patients may benefit from subsequent Wada testing or intraoperative language mapping.
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Affiliation(s)
- Justin M Campbell
- School of Medicine, University of Utah, Salt Lake City, Utah, USA
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, Utah, USA
| | - Bornali Kundu
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
| | - James N Lee
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Michelle Miranda
- Department of Neurology, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
| | - Amir Arain
- Department of Neurology, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
| | - Philipp Taussky
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Ramesh Grandhi
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - John D Rolston
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
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Nozais V, Forkel SJ, Petit L, Talozzi L, Corbetta M, Thiebaut de Schotten M, Joliot M. Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain. Commun Biol 2023; 6:726. [PMID: 37452124 PMCID: PMC10349117 DOI: 10.1038/s42003-023-05107-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 07/06/2023] [Indexed: 07/18/2023] Open
Abstract
Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.
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Affiliation(s)
- Victor Nozais
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France.
| | - Stephanie J Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Donders Institute for Brain Cognition Behaviour, Radboud University, Nijmegen, the Netherlands
- Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Departments of Neurosurgery, Technical University of Munich School of Medicine, Munich, Germany
| | - Laurent Petit
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
| | - Lia Talozzi
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Maurizio Corbetta
- Department of Neuroscience, Venetian Institute of Molecular Medicine and Padova Neuroscience Center, University of Padua, Padova, PD, 32122, Italy
| | - Michel Thiebaut de Schotten
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
| | - Marc Joliot
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
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Boerger TF, Pahapill P, Butts AM, Arocho-Quinones E, Raghavan M, Krucoff MO. Large-scale brain networks and intra-axial tumor surgery: a narrative review of functional mapping techniques, critical needs, and scientific opportunities. Front Hum Neurosci 2023; 17:1170419. [PMID: 37520929 PMCID: PMC10372448 DOI: 10.3389/fnhum.2023.1170419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/16/2023] [Indexed: 08/01/2023] Open
Abstract
In recent years, a paradigm shift in neuroscience has been occurring from "localizationism," or the idea that the brain is organized into separately functioning modules, toward "connectomics," or the idea that interconnected nodes form networks as the underlying substrates of behavior and thought. Accordingly, our understanding of mechanisms of neurological function, dysfunction, and recovery has evolved to include connections, disconnections, and reconnections. Brain tumors provide a unique opportunity to probe large-scale neural networks with focal and sometimes reversible lesions, allowing neuroscientists the unique opportunity to directly test newly formed hypotheses about underlying brain structural-functional relationships and network properties. Moreover, if a more complete model of neurological dysfunction is to be defined as a "disconnectome," potential avenues for recovery might be mapped through a "reconnectome." Such insight may open the door to novel therapeutic approaches where previous attempts have failed. In this review, we briefly delve into the most clinically relevant neural networks and brain mapping techniques, and we examine how they are being applied to modern neurosurgical brain tumor practices. We then explore how brain tumors might teach us more about mechanisms of global brain dysfunction and recovery through pre- and postoperative longitudinal connectomic and behavioral analyses.
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Affiliation(s)
- Timothy F. Boerger
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Peter Pahapill
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Alissa M. Butts
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
- Mayo Clinic, Rochester, MN, United States
| | - Elsa Arocho-Quinones
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Manoj Raghavan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Max O. Krucoff
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Biomedical Engineering, Medical College of Wisconsin, Marquette University, Milwaukee, WI, United States
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Zhang X, Xu M, Yang X, Yang Y. Individual Differences in Emotion Attenuation Brought by Indirect Replies Is Related to Resting-State Brain Activity. Brain Sci 2023; 13:1053. [PMID: 37508985 PMCID: PMC10377414 DOI: 10.3390/brainsci13071053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023] Open
Abstract
During daily conversations, people prefer indirect replies in face-threatening situations. Existent studies have indicated that recipients tend to perceive the information conveyed by indirect replies as negative and emotion regions are engaged in indirect replies processing in face-threatening situations. In this study, we examined whether indirect replies can reduce recipients' experience of negative emotion and what are the underlying cerebral structures that may give rise to individual differences in the effectiveness of such replies in attenuating negative emotion. Behavior ratings and resting-stating functional magnetic resonance imaging (rs-fMRI) techniques were combined to explore these questions. We created dialogues expressing refusal or negative opinion with direct/indirect replies. Participants were asked to rate their emotional valence and arousal when they received such replies. The rating scores were used to correlate with spontaneous brain activity. Results showed that indirect replies indeed attenuated recipients' negative emotion experience. Moreover, the left caudate, the right anterior cingulate cortex (rACC), and the connectivity of rACC and left medial prefrontal cortex (lmPFC) were found to be positively correlated to individual differences in such emotion attenuation. Our findings provide direct empirical evidence for the face-saving function of indirect replies and reveal that the intrinsic brain activities of emotion network and theory of mind (ToM) network are related to individual differences in such emotion attenuation.
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Affiliation(s)
- Xiuping Zhang
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Maoyao Xu
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Xiaohong Yang
- Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Yufang Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
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7
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Li XT, Allen JW, Hu R. Implementation of Automated Pipeline for Resting-State fMRI Analysis with PACS Integration. J Digit Imaging 2023; 36:1189-1197. [PMID: 36596936 PMCID: PMC10287855 DOI: 10.1007/s10278-022-00758-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 01/04/2023] Open
Abstract
In recent years, the quantity and complexity of medical imaging acquisition and processing have increased tremendously. The explosion in volume and need for advanced imaging analysis have led to the creation of numerous software programs, which have begun to be incorporated into clinical practice for indications such as automated stroke assessment, brain tumor perfusion processing, and hippocampal volume analysis. Despite these advances, there remains a need for specialized, custom-built software for advanced algorithms and new areas of research that is not widely available or adequately integrated in these "out-of-the-box" solutions. The purpose of this paper is to describe the implementation of an image-processing pipeline that is versatile and simple to create, which allows for rapid prototyping of image analysis algorithms and subsequent testing in a clinical environment. This pipeline uses a combination of Orthanc server, custom MATLAB code, and publicly available FMRIB Software Library and RestNeuMap tools to automatically receive and analyze resting-state functional MRI data collected from a custom filter on the MR scanner output. The processed files are then sent directly to Picture Archiving and Communications System (PACS) without the need for user input. This initial experience can serve as a framework for those interested in simple implementation of an automated pipeline customized to clinical needs.
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Affiliation(s)
- Xiao T Li
- Department of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA, USA.
| | - Jason W Allen
- Department of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA, USA
- Department of Neurology, Emory University Hospital, Atlanta, GA, USA
| | - Ranliang Hu
- Department of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA, USA
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BOLD fMRI and DTI fiber tracking for preoperative mapping of eloquent cerebral regions in brain tumor patients: impact on surgical approach and outcome. Neurol Sci 2023:10.1007/s10072-023-06667-2. [PMID: 36914833 DOI: 10.1007/s10072-023-06667-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 02/01/2023] [Indexed: 03/15/2023]
Abstract
PURPOSE Task-based BOLD fMRI and DTI-fiber tracking have become part of the routine presurgical work-up of brain tumor patients in many institutions. However, their potential impact on both surgical treatment and neurologic outcome remains unclear, in despite of the high costs and complex implementation. METHODS We retrospectively investigated whether performing fMRI and DTI-ft preoperatively substantially impacted surgical planning and patient outcome in a series of brain tumor patients. We assessed (i) the quality of fMRI and DTI-ft results, by using a scale of 0-2 (0 = failed mapping; 1 = intermediate confidence; 2 = good confidence), (ii) whether functional planning substantially contributed to defining the surgical strategy to be undertaken (i.e., no surgery, biopsy, or resection, with or without ESM), the surgical entry point and extent of resection, and (iii) the incidence of neurological deficits post-operatively. RESULTS Twenty-seven patients constituted the study population. The mean confidence rating was 1.9/2 for fMRI localization of the eloquent cortex and lateralization of the language function and 1.7/2 for DTI-ft results. Treatment strategy was altered in 33% (9/27) of cases. Surgical entry point was modified in 8% (2/25) of cases. The extent of resection was modified in 40% (10/25). One patient (1/25, 4%) developed one new functional deficit post-operatively. CONCLUSION Functional MR mapping - which must not be considered an alternative to ESM - has a critical role preoperatively, potentially modifying treatment strategy or increasing the neurosurgeons' confidence in the surgical approach hypothesized based on conventional imaging.
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Cirillo S, Battistella G, Castellano A, Sanvito F, Iadanza A, Bailo M, Barzaghi RL, Acerno S, Mortini P, Gorno-Tempini ML, Mandelli ML, Falini A. Comparison between inferior frontal gyrus intrinsic connectivity network and verb-generation task fMRI network for presurgical language mapping in healthy controls and in glioma patients. Brain Imaging Behav 2022; 16:2569-2585. [PMID: 35908147 DOI: 10.1007/s11682-022-00712-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/20/2022] [Indexed: 11/02/2022]
Abstract
Task-based functional MRI (tb-fMRI) represents an extremely valuable approach for the identification of language eloquent regions for presurgical mapping in patients with brain tumors. However, its routinely application is limited by patient-related factors, such as cognitive disability and difficulty in coping with long-time acquisitions, and by technical factors, such as lack of equipment availability for stimuli delivery. Resting-state fMRI (rs-fMRI) instead, allows the identification of distinct language networks in a 10-min acquisition without the need of performing active tasks and using specific equipment. Therefore, to test the feasibility of rs-fMRI as a preoperative mapping tool, we reconstructed a lexico-semantic intrinsic connectivity network (ICN) in healthy controls (HC) and in a case series of patients with gliomas and compared the organization of this language network with the one derived from tb-fMRI in the patient's group. We studied three patients with extra-frontal gliomas who underwent functional mapping with auditory verb-generation (AVG) task and rs-fMRI with a seed in the left inferior frontal gyrus (IFG). First, we identified the functional connected areas to the IFG in HC. We qualitatively compared these areas with those that showed functional activation in AVG task derived from Neurosynth meta-analysis. Last, in each patient we performed single-subject analyses both for rs- and tb-fMRI, and we evaluated the spatial overlap between the two approaches. In HC, the IFG-ICN network showed a predominant left fronto-temporal functional connectivity in regions overlapping with the AVG network derived from a meta-analysis. In two patients, rs- and tb-fMRI showed comparable patterns of activation in left fronto-temporal regions, with different levels of contralateral activations. The third patient could not accomplish the AVG task and thus it was not possible to make any comparison with the ICN. However, in this patient, task-free approach disclosed a consistent network of fronto-temporal regions as in HC, and additional parietal regions. Our preliminary findings support the value of rs-fMRI approach for presurgical mapping, particularly for identifying left fronto-temporal core language-related areas in glioma patients. In a preoperative setting, rs-fMRI approach could represent a powerful tool for the identification of eloquent language areas, especially in patients with language or cognitive impairments.
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Affiliation(s)
- Sara Cirillo
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Giovanni Battistella
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Antonella Castellano
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy. .,Vita-Salute San Raffaele University, Milan, Italy.
| | | | - Antonella Iadanza
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Michele Bailo
- Vita-Salute San Raffaele University, Milan, Italy.,Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Stefania Acerno
- Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Pietro Mortini
- Vita-Salute San Raffaele University, Milan, Italy.,Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA.,Department of Psychiatry and Behavioral Science, and Weill Institute for Neurosciences, UCSF, San Francisco, CA, 94158, USA
| | - Maria Luisa Mandelli
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Andrea Falini
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
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10
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Advanced Neuroimaging Approaches to Pediatric Brain Tumors. Cancers (Basel) 2022; 14:cancers14143401. [PMID: 35884462 PMCID: PMC9318188 DOI: 10.3390/cancers14143401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 07/08/2022] [Indexed: 12/10/2022] Open
Abstract
Simple Summary After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors. Abstract Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.
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Smirnov AS, Melnikova-Pitskhelauri TV, Sharaev MG, Yarkin VE, Turkin AM, Afandiev RM, Khasieva LM, Bernshtein AV, Pitskhelauri DI, Pronin IN. [Comparison of resting state and task-based functional MRI in preoperative mapping in patients with brain gliomas]. ZHURNAL VOPROSY NEIROKHIRURGII IMENI N. N. BURDENKO 2022; 86:33-40. [PMID: 35942835 DOI: 10.17116/neiro20228604133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
OBJECTIVE To analyze and compare the results of cerebral cortex mapping with task-based (tb-fMRI) and resting-state functional MRI in patients with glioma of eloquent cortical areas. MATERIAL AND METHODS There were 55 patients (24 men and 31 women aged 24 - 74 years, median 39) with glial tumors. In 26 patients, the tumor was located in motor areas. Twenty-nine patients had lesions of Broca and Wernicke's areas. All patients underwent preoperative tb-fMRI and rs-fMRI. Then, resection of tumor was carried out in all cases. RESULTS Comparison of fMRI and rs-fMRI activation maps was assessed by calculating the Dice coefficient for inclusive speech and motor cortex masks and exclusive masks without brainstem, cerebellum, subcortical nuclei. Inclusive Dice coefficient for motor cortex ranged from 0.11 to 0.50, for speech cortex - from 0.006 to 0.240 (p<0.05). In case of exclusive masks, this value ranged from 0.15 to 0.55 for motor cortex and from 0.004 to 0.205 for speech cortex (p<0.05). CONCLUSION When comparing the results of cortical mapping in patients with glial tumors, the use of hemispheric exclusive and inclusive masks did not significantly increase activation maps matching. Probably, low degree of correspondence was associated with different genesis of activations, as well as with high variability of speech cortex.
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Affiliation(s)
- A S Smirnov
- Burdenko Neurosurgery Center, Moscow, Russia
| | | | - M G Sharaev
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - V E Yarkin
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - A M Turkin
- Burdenko Neurosurgery Center, Moscow, Russia
| | | | - L M Khasieva
- Sechenov First Moscow State Medical University, Moscow, Russia
| | - A V Bernshtein
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | | | - I N Pronin
- Burdenko Neurosurgery Center, Moscow, Russia
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12
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Mekki Y, Guillemot V, Lemaitre H, Carrion-Castillo A, Forkel S, Frouin V, Philippe C. The genetic architecture of language functional connectivity. Neuroimage 2021; 249:118795. [PMID: 34929384 DOI: 10.1016/j.neuroimage.2021.118795] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 11/11/2021] [Accepted: 12/08/2021] [Indexed: 02/08/2023] Open
Abstract
Language is a unique trait of the human species, of which the genetic architecture remains largely unknown. Through language disorders studies, many candidate genes were identified. However, such complex and multifactorial trait is unlikely to be driven by only few genes and case-control studies, suffering from a lack of power, struggle to uncover significant variants. In parallel, neuroimaging has significantly contributed to the understanding of structural and functional aspects of language in the human brain and the recent availability of large scale cohorts like UK Biobank have made possible to study language via image-derived endophenotypes in the general population. Because of its strong relationship with task-based fMRI (tbfMRI) activations and its easiness of acquisition, resting-state functional MRI (rsfMRI) have been more popularised, making it a good surrogate of functional neuronal processes. Taking advantage of such a synergistic system by aggregating effects across spatially distributed traits, we performed a multivariate genome-wide association study (mvGWAS) between genetic variations and resting-state functional connectivity (FC) of classical brain language areas in the inferior frontal (pars opercularis, triangularis and orbitalis), temporal and inferior parietal lobes (angular and supramarginal gyri), in 32,186 participants from UK Biobank. Twenty genomic loci were found associated with language FCs, out of which three were replicated in an independent replication sample. A locus in 3p11.1, regulating EPHA3 gene expression, is found associated with FCs of the semantic component of the language network, while a locus in 15q14, regulating THBS1 gene expression is found associated with FCs of the perceptual-motor language processing, bringing novel insights into the neurobiology of language.
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Affiliation(s)
- Yasmina Mekki
- NeuroSpin, Institut Joliot, CEA - Université Paris-Saclay, Gif-Sur-Yvette, 91191, France.
| | - Vincent Guillemot
- Hub de Bioinformatique et Biostatistique, Département Biologie Computationnelle, Institut Pasteur, USR 3756 CNRS, Paris, France
| | - Hervé Lemaitre
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, CNRS UMR 5293, Université de Bordeaux, Centre Broca Nouvelle-Aquitaine, Bordeaux, France
| | | | - Stephanie Forkel
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, CNRS UMR 5293, Université de Bordeaux, Centre Broca Nouvelle-Aquitaine, Bordeaux, France; Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neurosciences, King's College London, UK
| | - Vincent Frouin
- NeuroSpin, Institut Joliot, CEA - Université Paris-Saclay, Gif-Sur-Yvette, 91191, France
| | - Cathy Philippe
- NeuroSpin, Institut Joliot, CEA - Université Paris-Saclay, Gif-Sur-Yvette, 91191, France.
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13
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Preoperative Assessment of Language Dominance through Combined Resting-State and Task-Based Functional Magnetic Resonance Imaging. J Pers Med 2021; 11:jpm11121342. [PMID: 34945814 PMCID: PMC8706548 DOI: 10.3390/jpm11121342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 12/03/2021] [Accepted: 12/07/2021] [Indexed: 11/17/2022] Open
Abstract
Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years, the resting-state fMRI (RS-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Twenty patients suffering from brain lesions close to supposed language-relevant cortical areas were included. RS-fMRI and task-based (TB-fMRI) were performed for the purpose of preoperative language assessment. TB-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language-critical and language-supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the TB-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice index. Thereby, the RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. In general, the results suggest that determining language dominance in the human brain is feasible both with TB-fMRI and RS-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.
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14
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Wu C, Ferreira F, Fox M, Harel N, Hattangadi-Gluth J, Horn A, Jbabdi S, Kahan J, Oswal A, Sheth SA, Tie Y, Vakharia V, Zrinzo L, Akram H. Clinical applications of magnetic resonance imaging based functional and structural connectivity. Neuroimage 2021; 244:118649. [PMID: 34648960 DOI: 10.1016/j.neuroimage.2021.118649] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/24/2021] [Accepted: 10/10/2021] [Indexed: 12/23/2022] Open
Abstract
Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.
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Affiliation(s)
- Chengyuan Wu
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, 909 Walnut Street, Third Floor, Philadelphia, PA 19107, USA; Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut Street, First Floor, Philadelphia, PA 19107, USA.
| | - Francisca Ferreira
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Michael Fox
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota, 2021 Sixth Street S.E., Minneapolis, MN 55455, USA.
| | - Jona Hattangadi-Gluth
- Department of Radiation Medicine and Applied Sciences, Center for Precision Radiation Medicine, University of California, San Diego, 3855 Health Sciences Drive, La Jolla, CA 92037, USA.
| | - Andreas Horn
- Neurology Department, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Charitéplatz 1, D-10117, Berlin, Germany.
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK.
| | - Joshua Kahan
- Department of Neurology, Weill Cornell Medicine, 525 East 68th Street, New York, NY, 10065, USA.
| | - Ashwini Oswal
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Mansfield Rd, Oxford OX1 3TH, UK.
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, 7200 Cambridge, Ninth Floor, Houston, TX 77030, USA.
| | - Yanmei Tie
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA; Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Vejay Vakharia
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK.
| | - Ludvic Zrinzo
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Harith Akram
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
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15
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Berro DH, Lemée JM, Leiber LM, Emery E, Menei P, Ter Minassian A. Overt speech critically changes lateralization index and did not allow determination of hemispheric dominance for language: an fMRI study. BMC Neurosci 2021; 22:74. [PMID: 34852787 PMCID: PMC8638205 DOI: 10.1186/s12868-021-00671-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 09/09/2021] [Indexed: 11/25/2022] Open
Abstract
Background Pre-surgical mapping of language using functional MRI aimed principally to determine the dominant hemisphere. This mapping is currently performed using covert linguistic task in way to avoid motion artefacts potentially biasing the results. However, overt task is closer to natural speaking, allows a control on the performance of the task, and may be easier to perform for stressed patients and children. However, overt task, by activating phonological areas on both hemispheres and areas involved in pitch prosody control in the non-dominant hemisphere, is expected to modify the determination of the dominant hemisphere by the calculation of the lateralization index (LI). Objective Here, we analyzed the modifications in the LI and the interactions between cognitive networks during covert and overt speech task. Methods Thirty-three volunteers participated in this study, all but four were right-handed. They performed three functional sessions consisting of (1) covert and (2) overt generation of a short sentence semantically linked with an audibly presented word, from which we estimated the “Covert” and “Overt” contrasts, and a (3) resting-state session. The resting-state session was submitted to spatial independent component analysis to identify language network at rest (LANG), cingulo-opercular network (CO), and ventral attention network (VAN). The LI was calculated using the bootstrapping method. Results The LI of the LANG was the most left-lateralized (0.66 ± 0.38). The LI shifted from a moderate leftward lateralization for the Covert contrast (0.32 ± 0.38) to a right lateralization for the Overt contrast (− 0.13 ± 0.30). The LI significantly differed from each other. This rightward shift was due to the recruitment of right hemispheric temporal areas together with the nodes of the CO. Conclusion Analyzing the overt speech by fMRI allowed improvement in the physiological knowledge regarding the coordinated activity of the intrinsic connectivity networks. However, the rightward shift of the LI in this condition did not provide the basic information on the hemispheric language dominance. Overt linguistic task cannot be recommended for clinical purpose when determining hemispheric dominance for language. Supplementary Information The online version contains supplementary material available at 10.1186/s12868-021-00671-y.
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Affiliation(s)
- David Hassanein Berro
- Department of Neurosurgery, University Hospital of Caen Normandy, Avenue de la Côte de Nacre, 14000, Caen, France. .,Normandie Univ, UNICAEN, CEA, CNRS, ISTCT/CERVOxy group, GIP Cyceron, Caen, France. .,INSERM, CRCINA, Team 17, IRIS building, Angers, France.
| | - Jean-Michel Lemée
- INSERM, CRCINA, Team 17, IRIS building, Angers, France.,Department of Neurosurgery, University Hospital of Angers, Angers, France
| | | | - Evelyne Emery
- Department of Neurosurgery, University Hospital of Caen Normandy, Avenue de la Côte de Nacre, 14000, Caen, France.,INSERM, UMR-S U1237, PhIND group, GIP Cyceron, Caen, France
| | - Philippe Menei
- INSERM, CRCINA, Team 17, IRIS building, Angers, France.,Department of Neurosurgery, University Hospital of Angers, Angers, France
| | - Aram Ter Minassian
- Department of Anesthesiology, University Hospital of Angers, Angers, France.,LARIS, ISISV team, University of Angers, Angers, France
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16
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Phillips NL, Shatil AS, Go C, Robertson A, Widjaja E. Resting-State Functional MRI for Determining Language Lateralization in Children with Drug-Resistant Epilepsy. AJNR Am J Neuroradiol 2021; 42:1299-1304. [PMID: 33832955 DOI: 10.3174/ajnr.a7110] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 02/16/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Task-based fMRI is a noninvasive method of determining language dominance; however, not all children can complete language tasks due to age, cognitive/intellectual, or language barriers. Task-free approaches such as resting-state fMRI offer an alternative method. This study evaluated resting-state fMRI for predicting language laterality in children with drug-resistant epilepsy. MATERIALS AND METHODS A retrospective review of 43 children with drug-resistant epilepsy who had undergone resting-state fMRI and task-based fMRI during presurgical evaluation was conducted. Independent component analysis of resting-state fMRI was used to identify language networks by comparing the independent components with a language network template. Concordance rates in language laterality between resting-state fMRI and each of the 4 task-based fMRI language paradigms (auditory description decision, auditory category, verbal fluency, and silent word generation tasks) were calculated. RESULTS Concordance ranged from 0.64 (95% CI, 0.48-0.65) to 0.73 (95% CI, 0.58-0.87), depending on the language paradigm, with the highest concordance found for the auditory description decision task. Most (78%-83%) patients identified as left-lateralized on task-based fMRI were correctly classified as left-lateralized on resting-state fMRI. No patients classified as right-lateralized or bilateral on task-based fMRI were correctly classified by resting-state fMRI. CONCLUSIONS While resting-state fMRI correctly classified most patients who had typical (left) language dominance, its ability to correctly classify patients with atypical (right or bilateral) language dominance was poor. Further study is required before resting-state fMRI can be used clinically for language mapping in the context of epilepsy surgery evaluation in children with drug-resistant epilepsy.
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Affiliation(s)
- N L Phillips
- From the Neurosciences and Mental Health Program (N.L.P., A.S.S., A.R., E.W.), The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, Ontario, Canada
- Department of Psychology (N.L.P.)
| | - A S Shatil
- From the Neurosciences and Mental Health Program (N.L.P., A.S.S., A.R., E.W.), The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, Ontario, Canada
| | - C Go
- Division of Neurology (C.G., E.W.)
| | - A Robertson
- From the Neurosciences and Mental Health Program (N.L.P., A.S.S., A.R., E.W.), The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, Ontario, Canada
| | - E Widjaja
- From the Neurosciences and Mental Health Program (N.L.P., A.S.S., A.R., E.W.), The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, Ontario, Canada
- Division of Neurology (C.G., E.W.)
- Department of Diagnostic Imaging (E.W.), The Hospital for Sick Children, Toronto, Ontario, Canada
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17
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Połczyńska MM. Organizing Variables Affecting fMRI Estimates of Language Dominance in Patients with Brain Tumors. Brain Sci 2021; 11:brainsci11060694. [PMID: 34070413 PMCID: PMC8226970 DOI: 10.3390/brainsci11060694] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 05/21/2021] [Accepted: 05/22/2021] [Indexed: 11/16/2022] Open
Abstract
Numerous variables can affect the assessment of language dominance using presurgical functional magnetic resonance (fMRI) in patients with brain tumors. This work organizes the variables into confounding and modulating factors. Confounding factors give the appearance of changed language dominance. Most confounding factors are fMRI-specific and they can substantially disrupt the evaluation of language dominance. Confounding factors can be divided into two categories: tumor-related and fMRI analysis. The tumor-related confounds further subdivide into tumor characteristics (e.g., tumor grade) and tumor-induced conditions (aphasia). The fMRI analysis confounds represent technical aspects of fMRI methods (e.g., a fixed versus an individual threshold). Modulating factors can modify language dominance without confounding it. They are not fMRI-specific, and they can impact language dominance both in healthy individuals and neurosurgical patients. The effect of most modulating factors on fMRI language dominance is smaller than that of confounding factors. Modulating factors include demographics (e.g., age) and linguistic variables (e.g., early bilingualism). Three cases of brain tumors in the left hemisphere are presented to illustrate how modulating confounding and modulating factors can impact fMRI estimates of language dominance. Distinguishing between confounding and modulating factors can help interpret the results of presurgical language mapping with fMRI.
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Affiliation(s)
- Monika M Połczyńska
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90025, USA
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18
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Jalilianhasanpour R, Beheshtian E, Ryan D, Luna LP, Agarwal S, Pillai JJ, Sair HI, Gujar SK. Role of Functional Magnetic Resonance Imaging in the Presurgical Mapping of Brain Tumors. Radiol Clin North Am 2021; 59:377-393. [PMID: 33926684 DOI: 10.1016/j.rcl.2021.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
When planning for brain tumor resection, a balance between maximizing resection and minimizing injury to eloquent brain parenchyma is paramount. The advent of blood oxygenation level-dependent functional magnetic resonance (fMR) imaging has allowed researchers and clinicians to reliably measure physiologic fluctuations in brain oxygenation related to neuronal activity with good spatial resolution. fMR imaging can offer a unique insight into preoperative planning for brain tumors by identifying eloquent areas of the brain affected or spared by the neoplasm. This article discusses the fMR imaging techniques and their applications in neurosurgical planning.
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Affiliation(s)
- Rozita Jalilianhasanpour
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA
| | - Elham Beheshtian
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA
| | - Daniel Ryan
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA
| | - Licia P Luna
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA
| | - Shruti Agarwal
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA
| | - Jay J Pillai
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans Street, Baltimore, MD 21287, USA
| | - Haris I Sair
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA; The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA
| | - Sachin K Gujar
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA.
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19
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Niu C, Cohen AD, Wen X, Chen Z, Lin P, Liu X, Menze BH, Wiestler B, Wang Y, Zhang M. Modeling motor task activation from resting-state fMRI using machine learning in individual subjects. Brain Imaging Behav 2021; 15:122-132. [PMID: 31903530 DOI: 10.1007/s11682-019-00239-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Resting-state functional MRI (rs-fMRI) has provided important insights into brain physiology. It has become an increasingly popular method for presurgical mapping, as an alternative to task-based functional MRI wherein the subject performs a task while being scanned. However, there is no commonly acknowledged gold standard approach for detecting eloquent brain areas using rs-fMRI data in clinical settings. In this study, a general linear model-based machine learning (GLM-ML) approach was tested to predict individual motor task activation based on rs-fMRI data. Its accuracy was then compared to a conventional independent component analysis (ICA) approach. 47 healthy subjects were scanned using resting state, active and passive motor task fMRI experiments using a clinically applicable low-resolution fMRI protocol. The model was trained to associate rs-fMRI network maps with that of hand movement task fMRI, then used to predict task activation maps for unseen subjects solely based on their rs-fMRI data. Our results showed that the GLM-ML approach can accurately predict individual differences in task activation using rs-fMRI data and outperform conventional ICA to detect task activation in the primary sensorimotor region. Furthermore, the predicted activation maps using the GLM -ML model matched well with the activation of passive hand movement fMRI on an individual basis. These results suggest that GLM-ML approach can robustly predict individual differences of task activation based on conventional low-resolution rs-fMRI data and has important implications for future clinical applications.
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Affiliation(s)
- Chen Niu
- Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 West Yanta Road, Xi'an, 710061, Shaanxi Province, China
- Institute for Biomedical Engineering, Technical University of Munich, Munich, Germany
| | - Alexander D Cohen
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Xin Wen
- Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 West Yanta Road, Xi'an, 710061, Shaanxi Province, China
| | - Ziyi Chen
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Pan Lin
- Department of Psychology and Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, China
| | - Xin Liu
- Institute for Biomedical Engineering, Technical University of Munich, Munich, Germany
| | - Bjoern H Menze
- Institute for Biomedical Engineering, Technical University of Munich, Munich, Germany
- Department of Computer Science, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum rechts der Isar, TU München, Munich, Germany
| | - Yang Wang
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Ming Zhang
- Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, No. 277 West Yanta Road, Xi'an, 710061, Shaanxi Province, China.
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20
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Duan G, He Q, Pang Y, Chen W, Liao H, Liu H, Tan L, Liu Y, Tao J, Zhang J, Wei X, Sun P, Liu P, Deng D. Altered amygdala resting-state functional connectivity following acupuncture stimulation at BaiHui (GV20) in first-episode drug-Naïve major depressive disorder. Brain Imaging Behav 2021; 14:2269-2280. [PMID: 31432318 DOI: 10.1007/s11682-019-00178-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Amygdala is an important locus of dysfunction implicated in major depressive disorder(MDD). Aberrant amygdala networks(AN) had been reported in resting-state functional magnetic resonance imaging (rs-fMRI) study. The safety and efficacy of acupuncture treatment for MDD have been verified in previous clinical studies. This study is aimed to investigate whether acupuncture at GV20 could modulate the abnormal AN of patients with the first-episode, drug-naïve MDD by using rs-fMRI combined with functional connectivity (FC) method. Thirty MDD patient underwent 6-min rs-fMRI scans respectively before and after 20-min electro-acupuncture stimulate(EAS) at GV20. Twenty-nine healthy subjects underwent only a 6-min rs-fMRI scan. Based on the amygdala as the seed region, FC method was adopted to examine abnormal AN in patients by comparing with healthy subjects and to evaluate the influence of EAS on intrinsic connectivity within the AN in patients with MDD. Compared to healthy subjects, MDD patients had aberrant intrinsic AN which mainly showed increased FC between amygdala and hippocampus, precuneus, precentral gyrus and angular gyrus, as well as decreased FC between amygdala and orbital frontal cortex(OFC). Moreover, our results indicated that EAS at GV20 induced increased/decreased FC between amygdala and certain regions in MDD patients. In addition, the intrinsic amygdala FC within other certain brain regions in MDD patients were regulated by EAS at GV20. The abnormal AN of MDD patients could be modulated by EAS at GV20. Our findings may further provide the potential imaging evidence to support the modulatory mechanisms of acupuncture on MDD.
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Affiliation(s)
- Gaoxiong Duan
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Qianchao He
- Department of Neurology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Yong Pang
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Wenfu Chen
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Hai Liao
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Huimei Liu
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Lulu Tan
- Department of Neurology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Yanfei Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China
| | - Jien Tao
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Jian Zhang
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Xiaomei Wei
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Peiyi Sun
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Peng Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China
| | - Demao Deng
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China.
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21
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van Lieshout J, Debaene W, Rapp M, Noordmans HJ, Rutten GJ. fMRI Resting-State Connectivity between Language and Nonlanguage Areas as Defined by Intraoperative Electrocortical Stimulation in Low-Grade Glioma Patients. J Neurol Surg A Cent Eur Neurosurg 2021; 82:357-363. [PMID: 33618418 DOI: 10.1055/s-0040-1721757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
BACKGROUND AND OBJECTIVES It remains to be determined whether noninvasive functional imaging techniques can rival the clinical potential of direct electrocortical stimulation (DES). In this study, we compared the results of resting-state functional magnetic resonance imaging (rs-fMRI) to those of DES for language mapping. Our goals were twofold: (1) to replicate a previous study that demonstrated that resting-state connectivity (RSC) was significantly larger between positive DES language sites than between negative DES language sites and (2) to compare the spatial resolution of rs-fMRI to that of DES. METHODS We conducted a retrospective study of nine low-grade glioma patients. Language sites were identified by intraoperative DES. We compared RSC values between and within groups of DES-positive and DES-negative regions of interest (ROIs). Both close-negative sites (i.e., DES-negative sites <1 cm apart from and on the same gyrus as DES-positive sites) and far-negative sites (i.e., purely randomly chosen sites not in the vicinity of the tumor or of the DES-positive sites but on the same lobe) were included. Receiver operating characteristics were used to quantify comparisons. RESULTS Functional connectivity between all positive language sites was on average significantly higher than between all close-negative sites and between all far-negative sites. The functional connectivity between the positive language ROIs and their respective close-negative control sites was not smaller than between all positive language sites. CONCLUSION rs-fMRI likely reflects similar neural information as detected with DES, but in its current form does not reach the spatial resolution of DES.
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Affiliation(s)
- Jasper van Lieshout
- Department of Neurosurgery, Universitatsklinikum Dusseldorf, Dusseldorf, Nordrhein-Westfalen, Germany
| | - Wouter Debaene
- Department of Cognitive Neuropsychology, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, Noord-Brabant, The Netherlands
| | - Marion Rapp
- Department of Neurosurgery, Universitatsklinikum Dusseldorf, Dusseldorf, Nordrhein-Westfalen, Germany
| | | | - Geert-Jan Rutten
- Department of Neurosurgery, Elisabeth-TweeSteden Ziekenhuis, Tilburg, The Netherlands
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22
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Manan HA, Franz EA, Yahya N. The utilisation of resting-state fMRI as a pre-operative mapping tool in patients with brain tumours in comparison to task-based fMRI and intraoperative mapping: A systematic review. Eur J Cancer Care (Engl) 2021; 30:e13428. [PMID: 33592671 DOI: 10.1111/ecc.13428] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 01/25/2021] [Accepted: 01/28/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is suggested to be a viable option for pre-operative mapping for patients with brain tumours. However, it remains an open issue whether the tool is useful in the clinical setting compared to task-based fMRI (T-fMRI) and intraoperative mapping. Thus, a systematic review was conducted to investigate the usefulness of this technique. METHODS A systematic literature search of rs-fMRI methods applied as a pre-operative mapping tool was conducted using the PubMed/MEDLINE and Cochrane Library electronic databases following PRISMA guidelines. RESULTS Results demonstrated that 50% (six out of twelve) of the studies comparing rs-fMRI and T-fMRI showed good concordance for both language and sensorimotor networks. In comparison to intraoperative mapping, 86% (six out of seven) studies found a good agreement to rs-fMRI. Finally, 87% (twenty out of twenty-three) studies agreed that rs-fMRI is a suitable and useful pre-operative mapping tool. CONCLUSIONS rs-fMRI is a promising technique for pre-operative mapping in assessing the functional brain areas. However, the agreement between rs-fMRI with other techniques, including T-fMRI and intraoperative maps, is not yet optimal. Studies to ascertain and improve the sophistication in pre-processing of rs-fMRI imaging data are needed.
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Affiliation(s)
- Hanani Abdul Manan
- Makmal Pemprosesan Imej Kefungsian (Functional Image Processing Laboratory, Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
| | - Elizabeth A Franz
- Department of Psychology and fMRIotago, University of Otago, Dunedin, New Zealand
| | - Noorazrul Yahya
- Diagnostic Imaging & Radiotherapy Program, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
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23
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Cohen AD, Yang B, Fernandez B, Banerjee S, Wang Y. Improved resting state functional connectivity sensitivity and reproducibility using a multiband multi-echo acquisition. Neuroimage 2021; 225:117461. [PMID: 33069864 PMCID: PMC10015256 DOI: 10.1016/j.neuroimage.2020.117461] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 09/20/2020] [Accepted: 10/12/2020] [Indexed: 02/04/2023] Open
Abstract
Recent advances in functional MRI techniques include multiband (MB) imaging and multi-echo (ME) imaging. In MB imaging multiple slices are acquired simultaneously leading to significant increases in temporal and spatial resolution. Multi-echo imaging enables multiple echoes to be acquired in one shot, where the ME images can be used to denoise the BOLD time series and increase BOLD sensitivity. In this study, resting state fMRI (rs-fMRI) data were collected using a combined MBME sequence and compared to an MB single echo sequence. In total, 29 subjects were imaged, and 18 of them returned within two weeks for repeat imaging. Participants underwent one MBME scan with three echoes and one MB scan with one echo. Both datasets were processed using standard denoising and advanced denoising. Advanced denoising included multi-echo independent component analysis (ME-ICA) for the MBME data and ICA-AROMA for the MB data. Resting state functional connectivity (RSFC) was evaluated using both selective seed-based and whole grey matter (GM) region-of-interest (ROI) based approaches. The reproducibility of connectivity metrics was also analyzed in the repeat subjects. In addition, functional connectivity density (FCD), a data-driven approach that counts the number of significant connections, both within a local cluster and globally, with each voxel was analyzed. Regardless of the standard or advanced denoising technique, all seed-based RSFC was significantly higher for MBME compared to MB. Much more GM ROI combinations showed significantly higher RSFC for MBME vs. MB. Reproducibility, evaluated using the dice coefficient was significantly higher for MBME relative to MB data. Finally, FCD was also higher for MBME vs. MB data. This study showed higher RSFC for MBME vs. MB data using selected seed-based, whole GM ROI-based, and data-driven approaches. Reproducibility found also higher for MBME data. Taken together, these results indicate that MBME is a promising technique for rs-fMRI.
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Affiliation(s)
- Alexander D Cohen
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States
| | | | | | | | - Yang Wang
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States.
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24
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Pur DR, Eagleson R, Lo M, Jurkiewicz MT, Andrade A, de Ribaupierre S. Presurgical brain mapping of the language network in pediatric patients with epilepsy using resting-state fMRI. J Neurosurg Pediatr 2021; 27:259-268. [PMID: 33418528 DOI: 10.3171/2020.8.peds20517] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 08/17/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Epilepsy affects neural processing and often causes intra- or interhemispheric language reorganization, rendering localization solely based on anatomical landmarks (e.g., Broca's area) unreliable. Preoperative brain mapping is necessary to weigh the risk of resection with the risk of postoperative deficit. However, the use of conventional mapping methods (e.g., somatosensory stimulation, task-based functional MRI [fMRI]) in pediatric patients is technically difficult due to low compliance and their unique neurophysiology. Resting-state fMRI (rs-fMRI), a "task-free" technique based on the neural activity of the brain at rest, has the potential to overcome these limitations. The authors hypothesized that language networks can be identified from rs-fMRI by applying functional connectivity analyses. METHODS Cases in which both task-based fMRI and rs-fMRI were acquired as part of the preoperative clinical protocol for epilepsy surgery were reviewed. Task-based fMRI consisted of 2 language tasks and 1 motor task. Resting-state fMRI data were acquired while the patients watched an animated movie and were analyzed using independent component analysis (i.e., data-driven method). The authors extracted language networks from rs-fMRI data by performing a similarity analysis with functionally defined language network templates via a template-matching procedure. The Dice coefficient was used to quantify the overlap. RESULTS Thirteen children underwent conventional task-based fMRI (e.g., verb generation, object naming), rs-fMRI, and structural imaging at 1.5T. The language components with the highest overlap with the language templates were identified for each patient. Language lateralization results from task-based fMRI and rs-fMRI mapping were comparable, with good concordance in most cases. Resting-state fMRI-derived language maps indicated that language was on the left in 4 patients (31%), on the right in 5 patients (38%), and bilateral in 4 patients (31%). In some cases, rs-fMRI indicated a more extensive language representation. CONCLUSIONS Resting-state fMRI-derived language network data were identified at the patient level using a template-matching method. More than half of the patients in this study presented with atypical language lateralization, emphasizing the need for mapping. Overall, these data suggest that this technique may be used to preoperatively identify language networks in pediatric patients. It may also optimize presurgical planning of electrode placement and thereby guide the surgeon's approach to the epileptogenic zone.
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Affiliation(s)
| | - Roy Eagleson
- 2Department of Electrical and Computer Engineering, Brain and Mind Institute, University of Western Ontario, London
| | - Marcus Lo
- 3Lawson Health Research Institute, London
| | - Michael T Jurkiewicz
- 4Department of Medical Imaging, Children's Hospital at London Health Sciences Centre, London; and
| | | | - Sandrine de Ribaupierre
- 6Clinical Neurological Sciences, London Health Sciences Centre, University of Western Ontario, London, Ontario, Canada
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25
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Smirnov AS, Melnikova-Pitskhelauri TV, Sharaev MG, Zhukov VY, Pogosbekyan EL, Afandiev RM, Bozhenko AA, Yarkin VE, Chekhonin IV, Buklina SB, Bykanov AE, Ogurtsova AA, Kulikov AS, Bernshtein AV, Burnaev EV, Pitskhelauri DI, Pronin IN. [Resting-state fMRI in preoperative non-invasive mapping in patients with left hemisphere glioma]. ZHURNAL VOPROSY NEĬROKHIRURGII IMENI N. N. BURDENKO 2020; 84:17-25. [PMID: 32759923 DOI: 10.17116/neiro20208404117] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Maximum resection and preservation of neurological function are main principles in surgery of brain tumors, especially glial neoplasms with diffuse growth. Therefore, exact localizing of eloquent brain areas is an important component in surgical planning ensuring optimal resection with minimal postoperative neurological deficit. Functional MRI is used to localize eloquent brain areas adjacent to the tumor. This paper is an initial stage in analysis of resting-state fMRI in assessment of functional changes of neuronal activity caused by brain gliomas of different localization. We report two patients with glial tumors localized within the precentral gyrus of the left hemisphere and near speech area. Considering data of task-based and resting-state fMRI, as well as direct cortical stimulation, we propose a methodology for assessing the overlap of activations obtained by these methods.
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Affiliation(s)
- A S Smirnov
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | - M G Sharaev
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - V Yu Zhukov
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | | | - A A Bozhenko
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - V E Yarkin
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | | | - S B Buklina
- Burdenko Neurosurgical Center, Moscow, Russia
| | - A E Bykanov
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | - A S Kulikov
- Burdenko Neurosurgical Center, Moscow, Russia
| | - A V Bernshtein
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - E V Burnaev
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | | | - I N Pronin
- Burdenko Neurosurgical Center, Moscow, Russia
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26
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Park KY, Lee JJ, Dierker D, Marple LM, Hacker CD, Roland JL, Marcus DS, Milchenko M, Miller-Thomas MM, Benzinger TL, Shimony JS, Snyder AZ, Leuthardt EC. Mapping language function with task-based vs. resting-state functional MRI. PLoS One 2020; 15:e0236423. [PMID: 32735611 PMCID: PMC7394427 DOI: 10.1371/journal.pone.0236423] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 07/06/2020] [Indexed: 01/21/2023] Open
Abstract
Background Use of functional MRI (fMRI) in pre-surgical planning is a non-invasive method for pre-operative functional mapping for patients with brain tumors, especially tumors located near eloquent cortex. Currently, this practice predominantly involves task-based fMRI (T-fMRI). Resting state fMRI (RS-fMRI) offers an alternative with several methodological advantages. Here, we compare group-level analyses of RS-fMRI vs. T-fMRI as methods for language localization. Purpose To contrast RS-fMRI vs. T-fMRI as techniques for localization of language function. Methods We analyzed data obtained in 35 patients who had both T-fMRI and RS-fMRI scans during the course of pre-surgical evaluation. The RS-fMRI data were analyzed using a previously trained resting-state network classifier. The T-fMRI data were analyzed using conventional techniques. Group-level results obtained by both methods were evaluated in terms of two outcome measures: (1) inter-subject variability of response magnitude and (2) sensitivity/specificity analysis of response topography, taking as ground truth previously reported maps of the language system based on intraoperative cortical mapping as well as meta-analytic maps of language task fMRI responses. Results Both fMRI methods localized major components of the language system (areas of Broca and Wernicke) although not with equal inter-subject consistency. Word-stem completion T-fMRI strongly activated Broca's area but also several task-general areas not specific to language. RS-fMRI provided a more specific representation of the language system. Conclusion We demonstrate several advantages of classifier-based mapping of language representation in the brain. Language T-fMRI activated task-general (i.e., not language-specific) functional systems in addition to areas of Broca and Wernicke. In contrast, classifier-based analysis of RS-fMRI data generated maps confined to language-specific regions of the brain.
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Affiliation(s)
- Ki Yun Park
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - John J. Lee
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Laura M. Marple
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Carl D. Hacker
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Jarod L. Roland
- Department of Neurosurgery, University of California San Francisco, San Francisco, California, United States of America
| | - Daniel S. Marcus
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Mikhail Milchenko
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Michelle M. Miller-Thomas
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Tammie L. Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Joshua S. Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
- * E-mail:
| | - Abraham Z. Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Eric C. Leuthardt
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, United States of America
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27
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Kumar VA, Heiba IM, Prabhu SS, Chen MM, Colen RR, Young AL, Johnson JM, Hou P, Noll K, Ferguson SD, Rao G, Lang FF, Schomer DF, Liu HL. The role of resting-state functional MRI for clinical preoperative language mapping. Cancer Imaging 2020; 20:47. [PMID: 32653026 PMCID: PMC7353792 DOI: 10.1186/s40644-020-00327-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 07/02/2020] [Indexed: 11/10/2022] Open
Abstract
Background Task-based functional MRI (tb-fMRI) is a well-established technique used to identify eloquent cortex, but has limitations, particularly in cognitively impaired patients who cannot perform language paradigms. Resting-state functional MRI (rs-fMRI) is a potential alternative modality for presurgical mapping of language networks that does not require task performance. The purpose of our study is to determine the utility of rs-fMRI for clinical preoperative language mapping when tb-fMRI is limited. Methods We retrospectively reviewed 134 brain tumor patients who underwent preoperative fMRI language mapping. rs-fMRI was post-processed with seed-based correlation (SBC) analysis, when language tb-fMRI was limited. Two neuroradiologists reviewed both the tb-fMRI and rs-fMRI results. Six neurosurgeons retrospectively rated the usefulness of rs-fMRI for language mapping in their patients. Results Of the 134 patients, 49 cases had limited tb-fMRI and rs-fMRI was post-processed. Two neuroradiologists found rs-fMRI beneficial for functional language mapping in 41(84%) and 43 (88%) cases respectively; Cohen’s kappa is 0.83, with a 95% confidence interval (0.61, 1.00). The neurosurgeons found rs-fMRI “definitely” useful in 26 cases (60%) and “somewhat” useful in 13 cases (30%) in locating potential eloquent language centers of clinical interest. Six unsuccessful rs-fMRI cases were due to: head motion (2 cases), nonspecific functionality connectivity outside the posterior language network (1 case), and an unknown system instability (3 cases). Conclusions This study is a proof of concept that shows SBC rs-fMRI may be a viable alternative for clinical language mapping when tb-fMRI is limited.
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Affiliation(s)
- Vinodh A Kumar
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Islam M Heiba
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sujit S Prabhu
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Melissa M Chen
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rivka R Colen
- Department of Diagnostic Radiology, The University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Angela L Young
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jason M Johnson
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ping Hou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kyle Noll
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sherise D Ferguson
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ganesh Rao
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Frederick F Lang
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Donald F Schomer
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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28
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Thomason ME. Development of Brain Networks In Utero: Relevance for Common Neural Disorders. Biol Psychiatry 2020; 88:40-50. [PMID: 32305217 PMCID: PMC7808399 DOI: 10.1016/j.biopsych.2020.02.007] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 01/05/2020] [Accepted: 02/05/2020] [Indexed: 01/27/2023]
Abstract
Magnetic resonance imaging, histological, and gene analysis approaches in living and nonliving human fetuses and in prematurely born neonates have provided insight into the staged processes of prenatal brain development. Increased understanding of micro- and macroscale brain network development before birth has spurred interest in understanding the relevance of prenatal brain development to common neurological diseases. Questions abound as to the sensitivity of the intrauterine brain to environmental programming, to windows of plasticity, and to the prenatal origin of disorders of childhood that involve disruptions in large-scale network connectivity. Much of the available literature on human prenatal neural development comes from cross-sectional or case studies that are not able to resolve the longitudinal consequences of individual variation in brain development before birth. This review will 1) detail specific methodologies for studying the human prenatal brain, 2) summarize large-scale human prenatal neural network development, integrating findings from across a variety of experimental approaches, 3) explore the plasticity of the early developing brain as well as potential sex differences in prenatal susceptibility, and 4) evaluate opportunities to link specific prenatal brain developmental processes to the forms of aberrant neural connectivity that underlie common neurological disorders of childhood.
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Affiliation(s)
- Moriah E Thomason
- Department of Child and Adolescent Psychiatry, Department of Population Health, and Neuroscience Institute, New York University Langone Health, New York, New York.
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29
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Coolen T, Wens V, Vander Ghinst M, Mary A, Bourguignon M, Naeije G, Peigneux P, Sadeghi N, Goldman S, De Tiège X. Frequency-Dependent Intrinsic Electrophysiological Functional Architecture of the Human Verbal Language Network. Front Integr Neurosci 2020; 14:27. [PMID: 32528258 PMCID: PMC7264165 DOI: 10.3389/fnint.2020.00027] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 04/16/2020] [Indexed: 11/13/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) allowed the spatial characterization of the resting-state verbal language network (vLN). While other resting-state networks (RSNs) were matched with their electrophysiological equivalents at rest and could be spectrally defined, such correspondence is lacking for the vLN. This magnetoencephalography (MEG) study aimed at defining the spatio-spectral characteristics of the neuromagnetic intrinsic functional architecture of the vLN. Neuromagnetic activity was recorded at rest in 100 right-handed healthy adults (age range: 18-41 years). Band-limited power envelope correlations were performed within and across frequency bands (θ, α, β, and low γ) from a seed region placed in the left Broca's area, using static orthogonalization as leakage correction. K-means clustering was used to segregate spatio-spectral clusters of resting-state functional connectivity (rsFC). Remarkably, unlike other RSNs, within-frequency long-range rsFC from the left Broca's area was not driven by one main carrying frequency but was characterized by a specific spatio-spectral pattern segregated along the ventral (predominantly θ and α) and dorsal (β and low-γ bands) vLN streams. In contrast, spatial patterns of cross-frequency vLN functional integration were spectrally more widespread and involved multiple frequency bands. Moreover, the static intrinsic functional architecture of the neuromagnetic human vLN involved clearly left-hemisphere-dominant vLN interactions as well as cross-network interactions with the executive control network and postero-medial nodes of the DMN. Overall, this study highlighted the involvement of multiple modes of within and cross-frequency power envelope couplings at the basis of long-range electrophysiological vLN functional integration. As such, it lays the foundation for future works aimed at understanding the pathophysiology of language-related disorders.
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Affiliation(s)
- Tim Coolen
- Laboratoire de Cartographie fonctionnelle du Cerveau, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium.,Department of Radiology, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Vincent Wens
- Laboratoire de Cartographie fonctionnelle du Cerveau, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium.,Magnetoencenphalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Marc Vander Ghinst
- Laboratoire de Cartographie fonctionnelle du Cerveau, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Alison Mary
- Neuropsychology & Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences, ULB-Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Mathieu Bourguignon
- Laboratoire de Cartographie fonctionnelle du Cerveau, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium.,BCBL-Basque Center on Cognition, Brain and Language, San Sebastian, Spain.,Laboratoire Cognition Langage et Développement, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Gilles Naeije
- Laboratoire de Cartographie fonctionnelle du Cerveau, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Philippe Peigneux
- Neuropsychology & Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences, ULB-Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Niloufar Sadeghi
- Department of Radiology, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Serge Goldman
- Laboratoire de Cartographie fonctionnelle du Cerveau, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium.,Magnetoencenphalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Xavier De Tiège
- Laboratoire de Cartographie fonctionnelle du Cerveau, ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium.,Magnetoencenphalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
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30
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Branco P, Seixas D, Castro SL. Mapping language with resting-state functional magnetic resonance imaging: A study on the functional profile of the language network. Hum Brain Mapp 2020; 41:545-560. [PMID: 31609045 PMCID: PMC7268076 DOI: 10.1002/hbm.24821] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 09/26/2019] [Accepted: 09/27/2019] [Indexed: 12/05/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rsfMRI) is a promising technique for language mapping that does not require task-execution. This can be an advantage when language mapping is limited by poor task performance, as is common in clinical settings. Previous studies have shown that language maps extracted with rsfMRI spatially match their task-based homologs, but no study has yet demonstrated the direct participation of the rsfMRI language network in language processes. This demonstration is critically important because spatial similarity can be influenced by the overlap of domain-general regions that are recruited during task-execution. Furthermore, it is unclear which processes are captured by the language network: does it map rather low-level or high-level (e.g., syntactic and lexico-semantic) language processes? We first identified the rsfMRI language network and then investigated task-based responses within its regions when processing stimuli of increasing linguistic content: symbols, pseudowords, words, pseudosentences and sentences. The language network responded only to language stimuli (not to symbols), and higher linguistic content elicited larger brain responses. The left fronto-parietal, the default mode, and the dorsal attention networks were examined and yet none showed language involvement. These findings demonstrate for the first time that the language network extracted through rsfMRI is able to map language in the brain, including regions subtending higher-level syntactic and semantic processes.
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Affiliation(s)
- Paulo Branco
- Centre for PsychologyUniversity of PortoPortoPortugal
- Department of BiomedicineUniversity of PortoPortoPortugal
| | - Daniela Seixas
- Department of BiomedicineUniversity of PortoPortoPortugal
| | - São L. Castro
- Centre for PsychologyUniversity of PortoPortoPortugal
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Hsu AL, Chen HSM, Hou P, Wu CW, Johnson JM, Noll KR, Prabhu SS, Ferguson SD, Kumar VA, Schomer DF, Chen JH, Liu HL. Presurgical resting-state functional MRI language mapping with seed selection guided by regional homogeneity. Magn Reson Med 2019; 84:375-383. [PMID: 31793025 DOI: 10.1002/mrm.28107] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 10/24/2019] [Accepted: 11/14/2019] [Indexed: 01/09/2023]
Abstract
PURPOSE Resting-state functional MRI (rs-FMRI) has shown potential for presurgical mapping of eloquent cortex when a patient's performance on task-based FMRI is compromised. The seed-based analysis is a practical approach for detecting rs-FMRI functional networks; however, seed localization remains challenging for presurgical language mapping. Therefore, we proposed a data-driven approach to guide seed localization for presurgical rs-FMRI language mapping. METHODS Twenty-six patients with brain tumors located in left perisylvian regions had undergone task-based FMRI and rs-FMRI before tumor resection. For the seed-based rs-FMRI language mapping, a seeding approach that integrates regional homogeneity and meta-analysis maps (RH+MA) was proposed to guide the seed localization. Canonical and task-based seeding approaches were used for comparison. The performance of the 3 seeding approaches was evaluated by calculating the Dice coefficients between each rs-FMRI language mapping result and the result from task-based FMRI. RESULTS With the RH+MA approach, selecting among the top 6 seed candidates resulted in the highest Dice coefficient for 81% of patients (21 of 26) and the top 9 seed candidates for 92% of patients (24 of 26). The RH+MA approach yielded rs-FMRI language mapping results that were in greater agreement with the results of task-based FMRI, with significantly higher Dice coefficients (P < .05) than that of canonical and task-based approaches within putative language regions. CONCLUSION The proposed RH+MA approach outperformed the canonical and task-based seed localization for rs-FMRI language mapping. The results suggest that RH+MA is a robust and feasible method for seed-based functional connectivity mapping in clinical practice.
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Affiliation(s)
- Ai-Ling Hsu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Henry Szu-Meng Chen
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ping Hou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Changwei W Wu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Center, Shuang Ho Hospital, New Taipei, Taiwan
| | - Jason M Johnson
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kyle R Noll
- Section of Neuropsychology, Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sujit S Prabhu
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sherise D Ferguson
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Vinodh A Kumar
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Donald F Schomer
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jyh-Horng Chen
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
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Oyegbile TO. The role of task-based neural activation research in understanding cognitive deficits in pediatric epilepsy. Epilepsy Behav 2019; 99:106332. [PMID: 31399340 DOI: 10.1016/j.yebeh.2019.05.028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 05/15/2019] [Accepted: 05/19/2019] [Indexed: 11/29/2022]
Abstract
Children with epilepsy can experience significant cognitive dysfunction that can lead to academic underachievement. Traditionally believed to be primarily due to the effects of factors such as the chronicity of epilepsy, medication effects, or the location of the primary epileptogenic lesion;, recent evidence has indicated that disruption of cognition-specific distributed neural networks may play a significant role as well. Specifically, over the last decade, researchers have begun to characterize the mechanisms underlying disrupted cognitive substrates by evaluating neural network abnormalities observed during specific cognitive tasks, using task-based functional magnetic resonance imaging (fMRI). This targeted review assesses the current literature investigating the relationship between neural network abnormalities and cognitive deficits in pediatric epilepsy. The findings indicate that there are indeed neural network abnormalities associated with deficits in executive function, language, processing speed, and memory. Overall, cognitive dysfunction in pediatric epilepsy is associated with a decrease in neural network activation/deactivation as well as increased recruitment of brain regions not typically related to the specific cognitive task under investigation. The research to date has focused primarily on children with focal epilepsy syndromes with small sample sizes and differing research protocols. More extensive research in children with a wider representation of epilepsy syndromes (including generalized epilepsy syndromes) is necessary to fully understand these relationships and begin to identify underlying cognitive phenotypes that may account for the variability observed across children with epilepsy. Furthermore, more uniformity in fMRI protocols and neuropsychological tasks would be ideal to advance this literature.
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Affiliation(s)
- Temitayo O Oyegbile
- Georgetown University Medical Center, Washington, D.C., United States of America.
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Zacà D, Jovicich J, Corsini F, Rozzanigo U, Chioffi F, Sarubbo S. ReStNeuMap: a tool for automatic extraction of resting-state functional MRI networks in neurosurgical practice. J Neurosurg 2019; 131:764-771. [DOI: 10.3171/2018.4.jns18474] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Accepted: 04/17/2018] [Indexed: 01/16/2023]
Abstract
OBJECTIVEResting-state functional MRI (rs-fMRI) represents a promising and cost-effective alternative to task-based fMRI for presurgical mapping. However, the lack of clinically streamlined and reliable rs-fMRI analysis tools has prevented wide adoption of this technique. In this work, the authors introduce an rs-fMRI processing pipeline (ReStNeuMap) for automatic single-patient rs-fMRI network analysis.METHODSThe authors provide a description of the rs-fMRI network analysis steps implemented in ReStNeuMap and report their initial experience with this tool after performing presurgical mapping in 6 patients. They verified the spatial agreement between rs-fMRI networks derived by ReStNeuMap and localization of activation with intraoperative direct electrical stimulation (DES).RESULTSThe authors automatically extracted rs-fMRI networks including eloquent cortex in spatial proximity with the resected lesion in all patients. The distance between DES points and corresponding rs-fMRI networks was less than 1 cm in 78% of cases for motor, 100% of cases for visual, 87.5% of cases for language, and 100% of cases for speech articulation mapping.CONCLUSIONSThe authors’ initial experience with ReStNeuMap showed good spatial agreement between presurgical rs-fMRI predictions and DES findings during awake surgery. The availability of the rs-fMRI analysis tools for clinicians aiming to perform noninvasive mapping of brain functional networks may extend its application beyond surgical practice.
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Affiliation(s)
- Domenico Zacà
- 1Center for Mind/Brain Sciences, University of Trento; and
| | - Jorge Jovicich
- 1Center for Mind/Brain Sciences, University of Trento; and
| | - Francesco Corsini
- 2Division of Neurosurgery, Structural and Functional Connectivity Lab Project, and
| | - Umberto Rozzanigo
- 3Department of Radiology, Neuroradiology Unit, “S. Chiara” Hospital, Trento, Italy
| | - Franco Chioffi
- 2Division of Neurosurgery, Structural and Functional Connectivity Lab Project, and
| | - Silvio Sarubbo
- 2Division of Neurosurgery, Structural and Functional Connectivity Lab Project, and
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Abstract
Functional MRI is a reliable, noninvasive technique which allows spatial mapping of the various functions like sensorimotor, language and vision in the brain. This is of immense help to the neurosurgeon in presurgical planning and intraoperative navigation in order to identify and preserve eloquent areas of the brain and minimize post-surgical neurological deficits. Using this technique in children pose unique challenges. This article discusses some of these challenges and how they can be overcome in successful application of this technique in pediatric patients.
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Smitha KA, Arun KM, Rajesh PG, Thomas B, Radhakrishnan A, Sarma PS, Kesavadas C. Resting fMRI as an alternative for task-based fMRI for language lateralization in temporal lobe epilepsy patients: a study using independent component analysis. Neuroradiology 2019; 61:803-810. [PMID: 31020344 DOI: 10.1007/s00234-019-02209-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 04/02/2019] [Indexed: 02/04/2023]
Abstract
PURPOSE Our aim is to investigate whether rs-fMRI can be used as an effective technique to study language lateralization. We aim to find out the most appropriate language network among different networks identified using ICA. METHODS Fifteen healthy right-handed subjects, sixteen left, and sixteen right temporal lobe epilepsy patients prospectively underwent MR scanning in 3T MRI (GE Discovery™ MR750w), using optimized imaging protocol. We obtained task-fMRI data using a visual-verb generation paradigm. Rs-fMRI and language-fMRI analysis were conducted using FSL software. Independent component analysis (ICA) was used to estimate rs-fMRI networks. Dice coefficient was calculated to examine the similarity in activated voxels of a common language template and the rs-fMRI language networks. Laterality index (LI) was calculated from the task-based language activation and rs-fMRI language network, for a range of LI thresholds at different z scores. RESULTS Measurement of hemispheric language dominance with rs-fMRI was highly concordant with task-fMRI results. Among the evaluated z scores for a range of LI thresholds, rs-fMRI yielded a maximum accuracy of 95%, a sensitivity of 83%, and specificity of 92.8% for z = 2 at 0.05 LI threshold. CONCLUSION The present study suggests that rs-fMRI networks obtained using ICA technique can be used as an alternative for task-fMRI language laterality. The novel aspect of the work is suggestive of optimal thresholds while applying rs-fMRI, is an important endeavor given that many patients with epilepsy have co-morbid cognitive deficits. Thus, an accurate method to determine language laterality without requiring a patient to complete the language task would be advantageous.
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Affiliation(s)
- K A Smitha
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - K M Arun
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - P G Rajesh
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Bejoy Thomas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Ashalatha Radhakrishnan
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - P Sankara Sarma
- Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Science and Technology, Trivandrum, Kerala, 695011, India
| | - C Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
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Amemiya S, Yamashita H, Takao H, Abe O. Integrated multi-echo denoising strategy improves identification of inherent language laterality. Magn Reson Med 2018; 81:3262-3271. [PMID: 30561807 DOI: 10.1002/mrm.27620] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Revised: 10/10/2018] [Accepted: 11/07/2018] [Indexed: 11/09/2022]
Abstract
PURPOSE Although increasingly used in both neuroscience and clinical studies, a major challenge facing resting-state FMRI (rs-FMRI) still lies in isolating BOLD signal fluctuations resulting from neuronal activity from noise. In this study, we investigated the effect of a newly proposed denoising approach, integrated multi-echo rs-FMRI analysis, on language mapping. METHODS Multiband multi-echo rs-FMRI data were acquired, along with language task FMRI that identified language areas in the left hemisphere of 12 subjects. The language laterality and specificity of the language mapping given by seed-based correlation analysis were compared among the rs-FMRI data sets pre-processed using 3 different approaches: multi-echo data with integrated multi-echo independent component analysis, denoising that uses the TE-dependency of each signal component to judge its origin, and multi-echo and single-echo data with conventional denoising. The laterality index was automatically computed without setting any threshold to minimize the arbitrariness and to ensure the generality of the result. RESULTS A repeated measures analysis of variance followed by post hoc tests showed that optimal combination of the 3-echo data succeeded in increasing the correlation within the targeted language system. With the physically principled multi-echo denoising approach, the integrated strategy further succeeded in revealing areas of synchronization more specific to the language system compared with conventional denoising approach, which eventually improved the identification of the laterality of the system. CONCLUSION By successfully reducing non-specific correlations spreading over the brain, integrated multi-echo approach improved language mapping and identification of the laterality of the system using rs-FMRI.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hiroshi Yamashita
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
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Yordanova YN, Cochereau J, Duffau H, Herbet G. Combining resting state functional MRI with intraoperative cortical stimulation to map the mentalizing network. Neuroimage 2018; 186:628-636. [PMID: 30500423 DOI: 10.1016/j.neuroimage.2018.11.046] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 11/02/2018] [Accepted: 11/26/2018] [Indexed: 10/27/2022] Open
Abstract
OBJECTIVE To infer the face-based mentalizing network from resting-state functional MRI (rsfMRI) using a seed-based correlation analysis with regions of interest identified during intraoperative cortical electrostimulation. METHODS We retrospectively included 23 patients in whom cortical electrostimulation induced transient face-based mentalizing impairment during 'awake' craniotomy for resection of a right-sided diffuse low-grade glioma. Positive stimulation sites were recorded and transferred to the patients' preoperative normalized MRI, and then used as seeds for subsequent seed-to-voxel functional connectivity analyses. The analyses, conducted with an uncorrected voxel-level p-value of 0.001 and a false-discovery-rate cluster-level p-value of 0.05, allowed identification of the cortical structures, functionally coupled with the mentalizing-related sites. RESULTS Two clusters of responsive stimulations were identified intraoperatively - one in the right dorsolateral prefrontal cortex (dlPFC, n = 13) and the other in the right inferior frontal gyrus (IFG, n = 10). A whole group level analysis revealed that stimulation sites correlated mainly with voxels located in the pars triangularis of the IFG, the dorsolateral and dorsomedial prefrontal cortices, the temporo-parietal junction, the posterior superior temporal sulcus, and the posterior inferior temporal/fusiform gyrus. Other analyses, taking into consideration the location of the responsive sites (IFG versus dlPFC cluster), highlighted only minor differences between both groups. CONCLUSIONS The present study successfully demonstrated the involvement of a large-scale neural network in the face-based mentalizing that strongly matches networks, classically identified using task-based fMRI paradigms. We thus validated the combination of rsfMRI and stimulation mapping as a powerful approach to identify functional networks in brain-damaged patients.
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Affiliation(s)
- Yordanka Nikolova Yordanova
- Department of Neurosurgery, 'Percy' Military Hospital, 101 avenue Henri Barbusse, 92140, Clamart, France; National Institute for Health and Medical Research (INSERM), U1051, Team "Plasticity of the Central Nervous System, Human Stem Cells and Glial Tumors", Institute for Neurosciences of Montpellier, France.
| | - Jérôme Cochereau
- Department of Neurosurgery, Gui de Chauliac Hospital, 80 avenue Augustin Fliche, 34295, France; National Institute for Health and Medical Research (INSERM), U1051, Team "Plasticity of the Central Nervous System, Human Stem Cells and Glial Tumors", Institute for Neurosciences of Montpellier, France.
| | - Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, 80 avenue Augustin Fliche, 34295, France; National Institute for Health and Medical Research (INSERM), U1051, Team "Plasticity of the Central Nervous System, Human Stem Cells and Glial Tumors", Institute for Neurosciences of Montpellier, France; University of Montpellier, France.
| | - Guillaume Herbet
- Department of Neurosurgery, Gui de Chauliac Hospital, 80 avenue Augustin Fliche, 34295, France; National Institute for Health and Medical Research (INSERM), U1051, Team "Plasticity of the Central Nervous System, Human Stem Cells and Glial Tumors", Institute for Neurosciences of Montpellier, France; University of Montpellier, France.
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Ulloa A, Horwitz B. Quantifying Differences Between Passive and Task-Evoked Intrinsic Functional Connectivity in a Large-Scale Brain Simulation. Brain Connect 2018; 8:637-652. [PMID: 30430844 DOI: 10.1089/brain.2018.0620] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Establishing a connection between intrinsic and task-evoked brain activities is critical because it would provide a way to map task-related brain regions in patients unable to comply with such tasks. A crucial question within this realm is to what extent the execution of a cognitive task affects the intrinsic activity of brain regions not involved in the task. Computational models can be useful to answer this question because they allow us to distinguish task from nontask neural elements while giving us the effects of task execution on nontask regions of interest at the neuroimaging level. The quantification of those effects in a computational model would represent a step toward elucidating the intrinsic versus task-evoked connection. In this study we used computational modeling and graph theoretical metrics to quantify changes in intrinsic functional brain connectivity due to task execution. We used our large-scale neural modeling framework to embed a computational model of visual short-term memory into an empirically derived connectome. We simulated a neuroimaging study consisting of 10 subjects performing passive fixation (PF), passive viewing (PV), and delayed match-to-sample (DMS) tasks. We used the simulated blood oxygen level-dependent functional magnetic resonance imaging time series to calculate functional connectivity (FC) matrices and used those matrices to compute several graph theoretical measures. After determining that the simulated graph theoretical measures were largely consistent with experiments, we were able to quantify the differences between the graph metrics of the PF condition and those of the PV and DMS conditions. Thus, we show that we can use graph theoretical methods applied to simulated brain networks to aid in the quantification of changes in intrinsic brain FC during task execution. Our results represent a step toward establishing a connection between intrinsic and task-related brain activities.
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Affiliation(s)
- Antonio Ulloa
- Brain Imaging and Modeling Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, Maryland.,Neural Bytes, Washington, District of Columbia
| | - Barry Horwitz
- Brain Imaging and Modeling Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, Maryland
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Sundermann B, Pfleiderer B, Minnerup H, Berger K, Douaud G. Interaction of Developmental Venous Anomalies with Resting-State Functional MRI Measures. AJNR Am J Neuroradiol 2018; 39:2326-2331. [PMID: 30385467 DOI: 10.3174/ajnr.a5847] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 08/25/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Functional MR imaging of the brain, used for both clinical and neuroscientific applications, relies on measuring fluctuations in blood oxygenation. Such measurements are susceptible to noise of vascular origin. The purpose of this study was to assess whether developmental venous anomalies, which are frequently observed normal variants, can bias fMRI measures by appearing as true neural signal. MATERIALS AND METHODS Large developmental venous anomalies (1 in each of 14 participants) were identified from a large neuroimaging cohort (n = 814). Resting-state fMRI data were decomposed using independent component analysis, a data-driven technique that creates distinct component maps representing aspects of either structured noise or true neural activity. We searched all independent components for maps that exhibited a spatial distribution of their signals following the topography of developmental venous anomalies. RESULTS Of the 14 developmental venous anomalies identified, 10 were clearly present in 17 fMRI independent components in total. While 9 (52.9%) of these 17 independent components were dominated by venous contributions and 2 (11.8%) by motion artifacts, 2 independent components (11.8%) showed partial neural signal contributions and 5 independent components (29.4%) unambiguously exhibited typical neural signal patterns. CONCLUSIONS Developmental venous anomalies can strongly resemble neural signal as measured by fMRI. They are thus a potential source of bias in fMRI analyses, especially when present in the cortex. This could impede interpretation of local activity in patients, such as in presurgical mapping. In scientific studies with large samples, developmental venous anomaly confounds could be mainly addressed using independent component analysis-based denoising.
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Affiliation(s)
- B Sundermann
- From the Nuffield Department of Clinical Neurosciences (B.S., G.D.), Oxford Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK .,Institute of Clinical Radiology (B.S., B.P.), Medical Faculty, University of Münster and University Hospital Münster, Münster, Germany
| | - B Pfleiderer
- Institute of Clinical Radiology (B.S., B.P.), Medical Faculty, University of Münster and University Hospital Münster, Münster, Germany
| | - H Minnerup
- Department of Epidemiology and Social Medicine (H.M., K.B.), University of Münster, Münster, Germany
| | - K Berger
- Department of Epidemiology and Social Medicine (H.M., K.B.), University of Münster, Münster, Germany
| | - G Douaud
- From the Nuffield Department of Clinical Neurosciences (B.S., G.D.), Oxford Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
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Liouta E, Katsaros VK, Stranjalis G, Leks E, Klose U, Bisdas S. Motor and language deficits correlate with resting state functional magnetic resonance imaging networks in patients with brain tumors. J Neuroradiol 2018; 46:199-206. [PMID: 30179690 DOI: 10.1016/j.neurad.2018.08.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 07/10/2018] [Accepted: 08/15/2018] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE Evidence of pre-operative resting state functional magnetic resonance (RS-fMRI) validation by correlating it with clinical pre-operative status in brain tumor patients is scarce. Our aim was to validate the functional relevance of RS-fMRI by investigating the association between RS-fMRI and pre-operative motor and language function performance in patients with brain tumor. MATERIALS AND METHODS Sixty-nine patients with brain tumors were prospectively recruited. Patients with tumors near precentral gyrus (n = 49) underwent assessment for apparent (paresis) and subtle (finger tapping) deficits. Patients with left frontal tumors in the vicinity of the inferior frontal gyrus (n = 29) underwent assessment for gross (aphasia) and mild language (phonological verbal fluency) deficits. RS-fMRI results were extracted by spatial independent component analysis (ICA). RESULTS Motor group: paretic patients showed significantly (P = 0.01) decreased BOLD signal in ipsilesional precentral gyrus when compared to contralesional one. Significantly (P < 0.01) lower BOLD signal was also observed in ipsilesional precentral gyrus of paretics when compared with the non-paretics. In asymptomatic patients, a strong positive correlation (r = 0.68, P < 0.01) between ipsilesional motor cortex BOLD signal and contralesional finger tapping performance was observed. Language group: patients with aphasia showed significantly (P = 0.01) decreased RS-fMRI BOLD signal in left BA 44 when compared with non- aphasics. In asymptomatic patients, a strong positive correlation (r = 0.72, P < 0.01) between BA 44 BOLD signal and phonological fluency performance was observed. CONCLUSIONS Our results showed that RS-fMRI BOLD signal of motor and language networks were significantly affected by the tumors implying the usefulness of the method for assessment of the underlying functions in brain tumors patients.
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Affiliation(s)
- Evangelia Liouta
- Department of Neurosurgery, University of Athens, "Evangelismos" Hospital, Athens, Greece; Department of Neuroradiology, University Hospital of Tübingen, Tübingen, Germany.
| | - Vasileios K Katsaros
- Department of Radiology, General Anti-Cancer and Oncological Hospital of Athens "St. Savvas", Athens, Greece; Department of Neurosurgery, University of Athens, "Evangelismos" Hospital, Athens, Greece; Department of Neuroradiology, University Hospital of Tübingen, Tübingen, Germany
| | - George Stranjalis
- Department of Neurosurgery, University of Athens, "Evangelismos" Hospital, Athens, Greece
| | - Edyta Leks
- Department of Biomedical Magnetic Resonance, University Hospital of Tübingen, Tübingen, Germany
| | - Uwe Klose
- Department of Neuroradiology, University Hospital of Tübingen, Tübingen, Germany
| | - Sotirios Bisdas
- Department of Neuroradiology, University Hospital of Tübingen, Tübingen, Germany; Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, UK; Institute of Neurology, University College London, London, UK
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41
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Wongsripuemtet J, Tyan AE, Carass A, Agarwal S, Gujar SK, Pillai JJ, Sair HI. Preoperative Mapping of the Supplementary Motor Area in Patients with Brain Tumor Using Resting-State fMRI with Seed-Based Analysis. AJNR Am J Neuroradiol 2018; 39:1493-1498. [PMID: 30002054 DOI: 10.3174/ajnr.a5709] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Accepted: 05/08/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The supplementary motor area can be a critical region in the preoperative planning of patients undergoing brain tumor resection because it plays a role in both language and motor function. While primary motor regions have been successfully identified using resting-state fMRI, there is variability in the literature regarding the identification of the supplementary motor area for preoperative planning. The purpose of our study was to compare resting-state fMRI to task-based fMRI for localization of the supplementary motor area in a large cohort of patients with brain tumors presenting for preoperative brain mapping. MATERIALS AND METHODS Sixty-six patients with brain tumors were evaluated with resting-state fMRI using seed-based analysis of hand and orofacial motor regions. Rates of supplementary motor area localization were compared with those in healthy controls and with localization results by task-based fMRI. RESULTS Localization of the supplementary motor area using hand motor seed regions was more effective than seeding using orofacial motor regions for both patients with brain tumor (95.5% versus 34.8%, P < .001) and controls (95.2% versus 45.2%, P < .001). Bilateral hand motor seeding was superior to unilateral hand motor seeding in patients with brain tumor for either side (95.5% versus 75.8%/75.8% for right/left, P < .001). No difference was found in the ability to identify the supplementary motor area between patients with brain tumors and controls. CONCLUSIONS In addition to task-based fMRI, seed-based analysis of resting-state fMRI represents an equally effective method for supplementary motor area localization in patients with brain tumors, with the best results obtained with bilateral hand motor region seeding.
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Affiliation(s)
- J Wongsripuemtet
- From the Russell H. Morgan Department of Radiology and Radiological Sciences (J.W., A.E.T., S.A., S.K.G., J.J.P., H.I.S.).,Department of Radiology (J.W.), Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - A E Tyan
- From the Russell H. Morgan Department of Radiology and Radiological Sciences (J.W., A.E.T., S.A., S.K.G., J.J.P., H.I.S.)
| | - A Carass
- Department of Computer Science and Department of Electrical and Computer Engineering (A.C.), Johns Hopkins University, Baltimore, Maryland
| | - S Agarwal
- From the Russell H. Morgan Department of Radiology and Radiological Sciences (J.W., A.E.T., S.A., S.K.G., J.J.P., H.I.S.)
| | - S K Gujar
- From the Russell H. Morgan Department of Radiology and Radiological Sciences (J.W., A.E.T., S.A., S.K.G., J.J.P., H.I.S.)
| | - J J Pillai
- From the Russell H. Morgan Department of Radiology and Radiological Sciences (J.W., A.E.T., S.A., S.K.G., J.J.P., H.I.S.).,Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - H I Sair
- From the Russell H. Morgan Department of Radiology and Radiological Sciences (J.W., A.E.T., S.A., S.K.G., J.J.P., H.I.S.)
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Pang Y, Liu H, Duan G, Liao H, Liu Y, Feng Z, Tao J, Zou Z, Du G, Wan R, Liu P, Deng D. Altered Brain Regional Homogeneity Following Electro-Acupuncture Stimulation at Sanyinjiao (SP6) in Women With Premenstrual Syndrome. Front Hum Neurosci 2018; 12:104. [PMID: 29904344 PMCID: PMC5990869 DOI: 10.3389/fnhum.2018.00104] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Accepted: 03/05/2018] [Indexed: 01/02/2023] Open
Abstract
Background: Premenstrual syndrome (PMS) is a menstrual cycle-related disorder which causes physical and mood changes prior to menstruation and is associated with the functional dysregulation of the brain. Acupuncture is an effective alternative therapy for treating PMS, and sanyinjiao (SP6) is one of the most common acupoints used for improving the symptoms of PMS. However, the mechanism behind acupuncture's efficacy for relieving PMS symptoms remains unclear. The aim of this study was to identify the brain response patterns induced by acupuncture at acupoint SP6 in patients with PMS. Materials and Methods: Twenty-three females with PMS were enrolled in this study. All patients underwent resting-state fMRI data collection before and after 6 min of electroacupuncture stimulation (EAS) at SP6. A regional homogeneity (ReHo) approach was used to compare patients' brain responses before and after EAS at SP6 using REST software. The present study was registered at http://www.chictr.org.cn, and the Clinical Trial Registration Number is ChiCTR-OPC-15005918. Results: EAS at SP6 elicited decreased ReHo value at the bilateral precuneus, right inferior frontal cortex (IFC) and left middle frontal cortex (MFC). In contrast, increased ReHo value was found at the bilateral thalamus, bilateral insula, left putamen and right primary somatosensory cortex (S1). Conclusions: Our study provides an underlying neuroimaging evidence that the aberrant neural activity of PMS patients could be regulated by acupuncture at SP6.
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Affiliation(s)
- Yong Pang
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Huimei Liu
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Gaoxiong Duan
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Hai Liao
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Yanfei Liu
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Zhuo Feng
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Jien Tao
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Zhuocheng Zou
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Guoxiang Du
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Rongchao Wan
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
| | - Peng Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Demao Deng
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, China
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Hsu AL, Hou P, Johnson JM, Wu CW, Noll KR, Prabhu SS, Ferguson SD, Kumar VA, Schomer DF, Hazle JD, Chen JH, Liu HL. IClinfMRI Software for Integrating Functional MRI Techniques in Presurgical Mapping and Clinical Studies. Front Neuroinform 2018; 12:11. [PMID: 29593520 PMCID: PMC5854683 DOI: 10.3389/fninf.2018.00011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 02/23/2018] [Indexed: 01/25/2023] Open
Abstract
Task-evoked and resting-state (rs) functional magnetic resonance imaging (fMRI) techniques have been applied to the clinical management of neurological diseases, exemplified by presurgical localization of eloquent cortex, to assist neurosurgeons in maximizing resection while preserving brain functions. In addition, recent studies have recommended incorporating cerebrovascular reactivity (CVR) imaging into clinical fMRI to evaluate the risk of lesion-induced neurovascular uncoupling (NVU). Although each of these imaging techniques possesses its own advantage for presurgical mapping, a specialized clinical software that integrates the three complementary techniques and promptly outputs the analyzed results to radiology and surgical navigation systems in a clinical format is still lacking. We developed the Integrated fMRI for Clinical Research (IClinfMRI) software to facilitate these needs. Beyond the independent processing of task-fMRI, rs-fMRI, and CVR mapping, IClinfMRI encompasses three unique functions: (1) supporting the interactive rs-fMRI mapping while visualizing task-fMRI results (or results from published meta-analysis) as a guidance map, (2) indicating/visualizing the NVU potential on analyzed fMRI maps, and (3) exporting these advanced mapping results in a Digital Imaging and Communications in Medicine (DICOM) format that are ready to export to a picture archiving and communication system (PACS) and a surgical navigation system. In summary, IClinfMRI has the merits of efficiently translating and integrating state-of-the-art imaging techniques for presurgical functional mapping and clinical fMRI studies.
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Affiliation(s)
- Ai-Ling Hsu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Ping Hou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jason M Johnson
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Changwei W Wu
- Graduate Institute of Humanities in Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kyle R Noll
- Section of Neuropsychology, Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sujit S Prabhu
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sherise D Ferguson
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vinodh A Kumar
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Donald F Schomer
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - John D Hazle
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jyh-Horng Chen
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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44
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Cochereau J, Deverdun J, Herbet G, Charroud C, Boyer A, Moritz-Gasser S, Le Bars E, Molino F, Bonafé A, Menjot de Champfleur N, Duffau H. Comparison between resting state fMRI networks and responsive cortical stimulations in glioma patients. Hum Brain Mapp 2018; 37:3721-3732. [PMID: 27246771 DOI: 10.1002/hbm.23270] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2015] [Revised: 05/01/2016] [Accepted: 05/17/2016] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES To validate the functional relevance of resting state networks (RSNs) by means of a comparison of resting state connectivity (RSC) between language regions elicited by direct cortical stimulation versus RSC between random regions; and to evaluate the accuracy of resting state fMRI in surgical planning by assessing the overlap between RSNs and intraoperative functional mapping results. METHODS Sensorimotor and language eloquent sites were identified by direct electrical cortical stimulation in 98 patients with a diffuse low-grade glioma. A seed to voxel analysis with inter-language stimulation point connectivity versus inter-random ROIs connectivity was performed (19 patients). An independant component analysis (ICA) was also applied to rsfMRI data. Language and sensorimotor components were selected over 20 independent components and compared to the corresponding stimulation points and resected cortex masks (31 and 90 patients, respectively). RESULTS Mean connectivity value between language seeds was significantly higher than the one between random seeds (0.68 ± 0.39 and 0.12 ± 0.21 respectively, P < 10-10 ). 96 ± 11% of sensorimotor stimulation points were located within 10 mm from sensorimotor ICA maps versus 92 ± 21% for language. 3.1 and 15% of resected cortex overlapped sensorimotor and language networks, respectively. Mean sensorimotor stimulation points and resected cortex z-scores were 2.0 ± 1.2 and -0.050 ± 0.60, respectively (P < 10-10 ). Mean language stimulation points and resected cortex z-scores were 1.6 ± 1.9 and 0.68 ± 0.91, respectively, P < 0.005. CONCLUSION The significantly higher RSC between language seeds than between random seeds validated the functional relevance of RSC. ICA partly succeeded to distinguish eloquent versus surgically removable areas and may be possibly used as a complementary tool to intraoperative mapping. Hum Brain Mapp 37:3721-3732, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Jérôme Cochereau
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Jérémy Deverdun
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Institut de Génomique Fonctionnelle, Unité UMR 5203 - INSERM U661 - Université Montpellier II - Université Montpellier I, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Guillaume Herbet
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
| | - Céline Charroud
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Anthony Boyer
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,University of Montpellier 2, LIRMM laboratory, DEMAR Team, CNRS, INRIA, Montpellier, 34095, France
| | - Sylvie Moritz-Gasser
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
| | - Emmanuelle Le Bars
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - François Molino
- Institut de Génomique Fonctionnelle, Unité UMR 5203 - INSERM U661 - Université Montpellier II - Université Montpellier I, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Alain Bonafé
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Nicolas Menjot de Champfleur
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Hugues Duffau
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
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Ghinda DC, Wu JS, Duncan NW, Northoff G. How much is enough-Can resting state fMRI provide a demarcation for neurosurgical resection in glioma? Neurosci Biobehav Rev 2017; 84:245-261. [PMID: 29198588 DOI: 10.1016/j.neubiorev.2017.11.019] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 11/20/2017] [Accepted: 11/27/2017] [Indexed: 01/09/2023]
Abstract
This study represents a systematic review of the insights provided by resting state functional MRI (rs-fMRI) use in the glioma population. Following PRISMA guidelines, 45 studies were included in the review and were classified in glioma-related neuronal changes (n=28) and eloquent area localization (n=17). Despite the heterogeneous nature of the studies, there is considerable evidence of diffuse functional reorganization occurring in the setting of gliomas with local and interhemispheric functional connectivity alterations involving different functional networks. The studies showed evidence of decreased long distance functional connectivity and increased global local efficiency occurring in the setting of gliomas. The tumour grade seems to correlate with distinct functional connectivity changes. Overall, there is a potential clinical utility of rs-fMRI for identifying the functional brain network disruptions occurring in the setting of gliomas. Further studies utilizing standardized analytical methods are required to elucidate the mechanism through which gliomas induce global changes in brain connectivity.
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Affiliation(s)
- Diana C Ghinda
- Ottawa Hospital Research Institute, University of Ottawa, Division of Neurosurgery, The Ottawa Hospital, 1053 Carling Avenue, Ottawa, ON, K1Y 4E9, Canada; Mind, Brain Imaging and Neuroethics, Canada Research Chair, EJLB-Michael Smith Chair for Neuroscience and Mental Health, Royal Ottawa Mental Health Centre, University of Ottawa Institute of Mental Health Research, 1145 Carling Avenue, Rm. 6435, Ottawa, ON, K1Z 7K4, Canada.
| | - Jin-Song Wu
- Glioma Surgery Division, Department of Neurological Surgery, Huashan Hospital, Fudan University, 518 Wuzhong E Rd, Shanghai, China.
| | - Niall W Duncan
- Brain and Consciousness Research Center, Taipei Medical University-Shuang Ho Hospital, 250 Wu-Xing Street, Taipei, 11031, Taiwan.
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics, Canada Research Chair, EJLB-Michael Smith Chair for Neuroscience and Mental Health, Royal Ottawa Mental Health Centre, University of Ottawa Institute of Mental Health Research, 1145 Carling Avenue, Rm. 6435, Ottawa, ON, K1Z 7K4, Canada; Mental Health Center/7th Hospital, Zhejiang University School of Medicine, 305 Tianmu Road, Hangzhou, Zhejiang Province, 310013, China.
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46
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Sair HI, Agarwal S, Pillai JJ. Application of Resting State Functional MR Imaging to Presurgical Mapping. Neuroimaging Clin N Am 2017; 27:635-644. [DOI: 10.1016/j.nic.2017.06.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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47
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Liao H, Duan G, Liu P, Liu Y, Pang Y, Liu H, Tang L, Tao J, Wen D, Li S, Liang L, Deng D. Altered fractional amplitude of low frequency fluctuation in premenstrual syndrome: A resting state fMRI study. J Affect Disord 2017; 218:41-48. [PMID: 28458114 DOI: 10.1016/j.jad.2017.04.045] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Revised: 02/28/2017] [Accepted: 04/23/2017] [Indexed: 12/11/2022]
Abstract
BACKGROUND Premenstrual syndrome (PMS) is becoming highly prevalent among female and is characterized by emotional, physical and behavior symptoms. Previous evidence suggested functional dysregulation of female brain was expected to be involved in the etiology of PMS. The aim of present study was to evaluate the alterations of spontaneous brain activity in PMS patients based on functional magnetic resonance imaging (fMRI). METHODS 20 PMS patients and 21 healthy controls underwent resting-state fMRI scanning during luteal phase. All participants were asked to complete a prospective daily record of severity of problems (DRSP) questionnaire. RESULTS Compared with healthy controls, the results showed that PMS patients had increased fALFF in bilateral precuneus, left hippocampus and left inferior temporal cortex, and decreased fALFF in bilateral anterior cingulate cortex (ACC) and cerebellum at luteal phase. Moreover, the DRSP scores of PMS patients were negatively correlated with the mean fALFF in ACC and positively correlated with the fALFF in precuneus. LIMITATIONS (1) the study did not investigate whether or not abnormal brain activity differences between groups in mid-follicular phase, and within-group changes. between phases.(2) it was relatively limited sample size and the participants were young; (3) fALFF could not provide us with more holistic information of brain network;(4) the comparisons of PMS and premenstrual dysphoric disorder (PMDD) were not involved in the study. CONCLUSIONS The present study shows abnormal spontaneous brain activity in PMS patients revealed by fALFF, which could provide neuroimaging evidence to further improve our understanding of the underlying neural mechanism of PMS.
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Affiliation(s)
- Hai Liao
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Gaoxiong Duan
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Peng Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yanfei Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yong Pang
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Huimei Liu
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Lijun Tang
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Jien Tao
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Danhong Wen
- Department of Teaching, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Shasha Li
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Lingyan Liang
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China
| | - Demao Deng
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, Guangxi 530023, China.
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Ivanova A, Zaidel E, Salamon N, Bookheimer S, Uddin LQ, de Bode S. Intrinsic functional organization of putative language networks in the brain following left cerebral hemispherectomy. Brain Struct Funct 2017; 222:3795-3805. [PMID: 28470553 DOI: 10.1007/s00429-017-1434-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Accepted: 04/25/2017] [Indexed: 02/07/2023]
Abstract
In rare cases of severe and intractable epilepsy, cerebral hemispherectomy is performed to arrest seizure activity and improve quality of life. The remaining hemisphere is often capable of supporting many cognitive functions post-surgery, although the outcome depends on the underlying etiology, hemisphere removed, and age of resection. The mechanisms underlying this massive reorganization are at present unknown. Here we examined intrinsic functional connectivity of putative language brain networks in four children after left cerebral hemispherectomy using resting-state functional magnetic resonance imaging (rsfMRI). We compared these functional systems to intrinsic language networks in 15 neurotypical controls using region-of-interest (ROI)-based functional connectivity analyses. In three out of four hemispherectomy patients, the ROI placed in the right inferior gyrus revealed a functional network that strongly resembled the right-hemisphere intrinsic language network observed in controls. This network typically comprised inferior frontal gyrus, superior temporal sulcus, and premotor regions. Quantitative ROI-to-ROI analyses revealed that functional connectivity between major nodes of the language network was significantly altered in all 4 examined patients. Overall, our data demonstrate that the pattern of functional connectivity within language networks is at least partially preserved in the intact right hemisphere of patients who underwent left hemispherectomy.
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Affiliation(s)
- Anna Ivanova
- Department of Psychology, University of Miami, P.O. Box 248185, Coral Gables, FL, 33124, USA
| | - Eran Zaidel
- Department of Psychology, UCLA, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Susan Bookheimer
- Department of Radiology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, P.O. Box 248185, Coral Gables, FL, 33124, USA. .,Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA.
| | - Stella de Bode
- The Brain Recovery Project, Los Angeles, CA, USA.,CTC Widney, Los Angeles, CA, USA
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Yahyavi-Firouz-Abadi N, Pillai JJ, Lindquist MA, Calhoun VD, Agarwal S, Airan RD, Caffo B, Gujar SK, Sair HI. Presurgical Brain Mapping of the Ventral Somatomotor Network in Patients with Brain Tumors Using Resting-State fMRI. AJNR Am J Neuroradiol 2017; 38:1006-1012. [PMID: 28364005 DOI: 10.3174/ajnr.a5132] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2016] [Accepted: 12/25/2016] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Resting-state fMRI readily identifies the dorsal but less consistently the ventral somatomotor network. Our aim was to assess the relative utility of resting-state fMRI in the identification of the ventral somatomotor network via comparison with task-based fMRI in patients with brain tumor. MATERIALS AND METHODS We identified 26 surgically naïve patients referred for presurgical fMRI brain mapping who had undergone both satisfactory ventral motor activation tasks and resting-state fMRI. Following standard preprocessing for task-based fMRI and resting-state fMRI, general linear model analysis of the ventral motor tasks and independent component analysis of resting-state fMRI were performed with the number of components set to 20, 30, 40, and 50. Visual overlap of task-based fMRI and resting-state fMRI at different component levels was assessed and categorized as full match, partial match, or no match. Rest-versus-task-fMRI concordance was calculated with Dice coefficients across varying fMRI thresholds before and after noise removal. Multithresholded Dice coefficient volume under the surface was calculated. RESULTS The ventral somatomotor network was identified in 81% of patients. At the subject level, better matches between resting-state fMRI and task-based fMRI were seen with an increasing order of components (53% of cases for 20 components versus 73% for 50 components). Noise-removed group-mean volume under the surface improved as component numbers increased from 20 to 50, though ANOVA demonstrated no statistically significant difference among the 4 groups. CONCLUSIONS In most patients, the ventral somatomotor network can be identified with an increase in the probability of a better match at a higher component number. There is variable concordance of the ventral somatomotor network at the single-subject level between resting-state and task-based fMRI.
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Affiliation(s)
- N Yahyavi-Firouz-Abadi
- From the Department of Radiology (N.Y.-F.-A.), Mid-Atlantic Permanente Medical Group of Kaiser Permanente, Kensington, Maryland .,Division of Neuroradiology, (N.Y.-F.-A., J.J.P., S.A., R.D.A., S.K.G., H.I.S.), The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - J J Pillai
- Division of Neuroradiology, (N.Y.-F.-A., J.J.P., S.A., R.D.A., S.K.G., H.I.S.), The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - M A Lindquist
- Department of Biostatistics (M.A.L., B.C.), Johns Hopkins University, Baltimore, Maryland
| | - V D Calhoun
- The Mind Research Network (S.A., V.D.C.), Departments of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico
| | - S Agarwal
- Division of Neuroradiology, (N.Y.-F.-A., J.J.P., S.A., R.D.A., S.K.G., H.I.S.), The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.,The Mind Research Network (S.A., V.D.C.), Departments of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico
| | - R D Airan
- Division of Neuroradiology, (N.Y.-F.-A., J.J.P., S.A., R.D.A., S.K.G., H.I.S.), The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - B Caffo
- Department of Biostatistics (M.A.L., B.C.), Johns Hopkins University, Baltimore, Maryland
| | - S K Gujar
- Division of Neuroradiology, (N.Y.-F.-A., J.J.P., S.A., R.D.A., S.K.G., H.I.S.), The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - H I Sair
- Division of Neuroradiology, (N.Y.-F.-A., J.J.P., S.A., R.D.A., S.K.G., H.I.S.), The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
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Smitha KA, Akhil Raja K, Arun KM, Rajesh PG, Thomas B, Kapilamoorthy TR, Kesavadas C. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks. Neuroradiol J 2017; 30:305-317. [PMID: 28353416 DOI: 10.1177/1971400917697342] [Citation(s) in RCA: 327] [Impact Index Per Article: 46.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.
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Affiliation(s)
- K A Smitha
- 1 Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Science and Technology, India
| | - K Akhil Raja
- 1 Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Science and Technology, India
| | - K M Arun
- 1 Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Science and Technology, India
| | - P G Rajesh
- 2 Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, India
| | - Bejoy Thomas
- 1 Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Science and Technology, India
| | - T R Kapilamoorthy
- 1 Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Science and Technology, India
| | - Chandrasekharan Kesavadas
- 1 Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Science and Technology, India
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